Total Fertility Rate by Country: Comparing Global Birth Patterns

by StatRanker April 29, 2025 6415 47 min read

Demography snapshot • 2025 view using latest official releases

Total fertility rate (TFR) is the average number of children a woman would have over her lifetime if today’s age-specific birth rates stayed the same. It is designed for cross-country comparison because it is less distorted by a country’s age structure than crude birth rates.

Global TFR: ~2.2–2.3 Replacement level: ~2.1 (higher where mortality is higher) Ultra-low example: South Korea ~0.7 High-fertility leaders: ~5–6+

Updated: 2026-02-20 • Data window: latest available (mostly 2022–2024; used as a 2025 snapshot)

Top 10 countries by total fertility rate (≈2024–2025)

Rounded, harmonised estimates for comparability (latest available year in the 2022–2024 window).

Rank	Country	TFR (births per woman)	Interpretation
1	Niger	≈ 6.1	Very high-fertility
2	Somalia	≈ 6.1	Very high-fertility
3	Chad	≈ 6.0	Very high-fertility
4	Democratic Republic of the Congo	≈ 5.5	High-fertility
5	Mali	≈ 5.4	High-fertility
6	Central African Republic	≈ 5.3	High-fertility
7	Angola	≈ 5.3	High-fertility
8	Benin	≈ 5.2	High-fertility
9	Uganda	≈ 5.1	High-fertility
10	Burundi	≈ 4.9	High-fertility

Values are indicative and rounded to one decimal. A country can have a low TFR and still see many births in absolute terms if its population is large.

Bar chart: high-fertility leaders vs a world close to replacement

The dashed reference is the global average (~2.2). If the chart fails to load, the values are listed below.

Fallback list (Top 10):

Niger — ≈ 6.1
Somalia — ≈ 6.1
Chad — ≈ 6.0
DR Congo — ≈ 5.5
Mali — ≈ 5.4
Central African Republic — ≈ 5.3
Angola — ≈ 5.3
Benin — ≈ 5.2
Uganda — ≈ 5.1
Burundi — ≈ 4.9

Methodology (how this 2025 snapshot is built)

What TFR measures, where the numbers come from, and why “latest available” matters.

Total fertility rate (TFR) aggregates age-specific fertility rates into a single indicator: the expected number of live births per woman if current age-specific rates persist. Because it standardises for age structure, TFR is more suitable than crude birth rates for comparing countries at different demographic stages.

For a “2025” article, the key practical constraint is publication lag: the most complete, harmonised country series are typically available for 2022–2024, depending on the provider and national statistical release schedules. This update therefore uses the latest official estimates in that window as a proxy for 2025 conditions, and rounds values to improve comparability across sources and base years.

Primary reference databases include the UN Population Division (World Population Prospects) and the World Bank’s World Development Indicators. Long-run context and cross-checks are commonly taken from Our World in Data and national statistical agencies for countries with ultra-low fertility.

Limitations: (1) revisions happen when new survey/census inputs arrive; (2) TFR is a period measure and can temporarily drop during postponement of births; (3) replacement level varies with mortality and the sex ratio at birth; (4) territories and special administrative regions may use separate statistical systems.

Insights: why the gap between high- and low-fertility regimes keeps widening

A few structural patterns explain most of today’s global fertility map.

High fertility is now highly concentrated. TFR above 4 is increasingly limited to a cluster of low-income countries, largely in Sub-Saharan Africa. These countries typically have very young age structures and fast-growing school-age cohorts.
Ultra-low fertility is becoming normal in parts of East Asia and Europe. South Korea’s record-low TFR around 0.72 in 2023 illustrates how housing costs, work-family constraints, and delayed marriage can translate into persistently low births.
Middle-income “replacement crossover” has accelerated. Many countries that were above 2.1 a generation ago now sit close to or below replacement. The result is a demographic divergence: child-dependency challenges at the top of the table, ageing-dependency challenges at the bottom.

What this means for readers

How to interpret fertility patterns without turning them into stereotypes or headlines.

Fertility affects the economy mostly through age structure. High-fertility countries tend to face pressure on education systems, entry-level jobs, and basic infrastructure. Low-fertility countries face a different arithmetic: slower labour-force growth, rising old-age dependency, and more fiscal weight on pensions and health care.

For individuals, the practical signals are indirect but real: migration incentives often rise where labour shortages appear; housing markets and childcare availability become central to family decisions; and long-term investment themes shift toward productivity, automation, and elder-care services as populations age.

The most useful way to read TFR rankings is not “who is highest/lowest”, but which direction a country is moving and how quickly its age structure is changing. The next block provides a league-table excerpt with a youth-share indicator to make that change visible.

Why can a country rank low on TFR but still have many births?

Because births depend on both fertility and the number of women in child-bearing ages. Large countries can have low TFR yet produce many births in absolute terms. TFR is best read as “births per woman”, not “births in total”.

Is 2.1 always the replacement level?

It is a common benchmark for high-income settings, but the true replacement level can be higher in places with higher mortality or different sex ratios at birth. Replacement is a concept about long-run population stability without migration, not a universal biological constant.

Why are some places below 1.0 births per woman?

Ultra-low fertility often reflects a mix of delayed family formation, high housing and childcare costs, long work hours, and unequal distribution of care work. Policy incentives can help at the margin, but sustained change usually requires broader shifts in work-family compatibility.

Is TFR the same as “birth rate per 1,000 people”?

No. The crude birth rate measures births per 1,000 people in a year and is heavily influenced by how young or old the population is. TFR standardises across ages, which is why it is preferred for cross-country comparisons.

Does lower fertility automatically mean economic decline?

Not automatically. Low fertility creates headwinds for labour-force growth, but countries can offset them through productivity gains, later retirement, higher labour-force participation, and migration. The economic outcome depends on policy and adaptation speed.

What’s the biggest mistake when comparing countries?

Treating one year as destiny. TFR can shift with timing effects and revisions. A better comparison looks at multi-year trends and connects fertility to age structure, which is why the next block pairs TFR with the share of population under 15.

Next block continues with the league table excerpt and a scatter chart.

Next: League table & scatter →

League table excerpt: fertility rate and the share of population under 15

This excerpt pairs TFR with the youth share (population under age 15). In most countries, higher fertility aligns with a younger population — and with very different education, jobs, and dependency-ratio pressures than ageing societies.

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Rows

Approx. rank	Country	TFR (births per woman)	Under-15 share (%)
1	Niger	≈ 6.1	≈ 49
2	Somalia	≈ 6.1	≈ 47
3	Chad	≈ 6.0	≈ 46
4	DR Congo	≈ 5.5	≈ 46
5	Mali	≈ 5.4	≈ 47
6	Central African Republic	≈ 5.3	≈ 45
7	Angola	≈ 5.3	≈ 47
8	Benin	≈ 5.2	≈ 44
9	Uganda	≈ 5.1	≈ 48
10	Nigeria	≈ 4.6	≈ 43
11	Mozambique	≈ 4.5	≈ 44
12	Tanzania	≈ 4.4	≈ 44
13	Zambia	≈ 4.3	≈ 45
14	Guinea	≈ 4.2	≈ 43
15	Sudan	≈ 4.2	≈ 41
16	Burkina Faso	≈ 4.1	≈ 44
17	Madagascar	≈ 3.9	≈ 41
18	Cameroon	≈ 3.8	≈ 41
19	Senegal	≈ 3.8	≈ 41
20	Yemen	≈ 3.7	≈ 39
25	Afghanistan	≈ 3.6	≈ 44
28	Pakistan	≈ 3.3	≈ 35
30	Kenya	≈ 3.2	≈ 39
32	Ghana	≈ 3.1	≈ 37
34	Egypt	≈ 2.8	≈ 33
35	Philippines	≈ 2.7	≈ 31
36	Bolivia	≈ 2.6	≈ 31
38	Guatemala	≈ 2.5	≈ 33
40	India	≈ 2.0	≈ 26
41	Indonesia	≈ 2.1	≈ 25
42	Bangladesh	≈ 2.0	≈ 26
44	Morocco	≈ 2.3	≈ 27
45	Algeria	≈ 2.8	≈ 29
46	Iran	≈ 1.9	≈ 23
47	Turkey	≈ 1.9	≈ 23
48	Brazil	≈ 1.6	≈ 23
49	Mexico	≈ 1.7	≈ 26
50	South Africa	≈ 2.3	≈ 28
70	United States	≈ 1.6	≈ 18
72	United Kingdom	≈ 1.6	≈ 17
73	France	≈ 1.7	≈ 18
74	Sweden	≈ 1.7	≈ 18
75	Norway	≈ 1.6	≈ 18
76	Canada	≈ 1.5	≈ 16
77	Australia	≈ 1.6	≈ 18
78	Germany	≈ 1.4	≈ 14
79	Netherlands	≈ 1.5	≈ 16
80	Spain	≈ 1.3	≈ 15
81	Italy	≈ 1.2	≈ 13
82	Portugal	≈ 1.4	≈ 14
83	Poland	≈ 1.2	≈ 15
84	Russia	≈ 1.4	≈ 18
85	Ukraine	≈ 1.1	≈ 15
86	China	≈ 1.2	≈ 17
87	Thailand	≈ 1.2	≈ 17
88	Vietnam	≈ 1.8	≈ 23
89	Japan	≈ 1.3	≈ 12
90	South Korea	≈ 0.7	≈ 12
91	Singapore	≈ 1.0	≈ 13
92	Hong Kong SAR	≈ 0.9	≈ 13
93	Taiwan	≈ 0.9	≈ 13

Source window: 2022–2024 harmonised estimates (used as a 2025 snapshot). Table shows a compact excerpt with rounded values.

Scatter chart: TFR and youth share move together

Each dot is a country from the table. The x-axis is TFR; the y-axis is the share of population under 15. The chart is built directly from the table rows.

If the scatter chart does not render, the table above contains the full data used for the plot.

← Back: Overview

Next: Interpretation & sources →

Interpretation: what fertility rankings do (and do not) tell you

TFR is powerful because it compresses a complex age-specific distribution into one number. But it should be read together with age structure, migration, and the timing of births.

How to read the extremes

Countries at the top of the TFR table tend to be early in the demographic transition: child-dependency dominates, school-age cohorts grow quickly, and the binding constraint is often education capacity, basic health systems, and the speed of job creation.

Countries at the bottom are usually in late-transition or post-transition phases: ageing accelerates, labour-force growth slows, and the binding constraint becomes productivity, work-family compatibility, and long-run fiscal design (pensions, health care, and care-work systems).

Policy takeaways (high-fertility settings)

Shift from “more births” to “better outcomes per child”: the biggest returns come from child survival, schooling quality, and women’s education.
Modern contraception and spacing: expanding access typically reduces unintended births and improves maternal/infant health.
Jobs matter as much as services: youth-heavy age structures turn into opportunity only when labour markets can absorb new entrants.

Policy takeaways (low-fertility settings)

Make family formation compatible with careers: predictable childcare, flexible work arrangements, and fair parental leave are often more important than one-off bonuses.
Housing and time costs: when young adults face high housing costs and long work hours, fertility tends to stay low even under generous incentives.
Adapt to ageing: later retirement, higher participation, productivity growth, and well-designed migration policy are common pillars in ageing societies.

Common pitfalls

Period vs completed fertility: TFR can fall temporarily when people postpone births, even if they still want children later.
Age structure confusions: crude birth rates drop when populations age — even if behaviour within age groups changes little.
Single-year comparisons: revisions and timing effects matter; trends are more informative than one point in time.

Sources (primary links)

UN DESA Population Division — World Population Prospects (WPP)

Core international source for country fertility estimates and long-run projections.
population.un.org/wpp/
World Bank — World Development Indicators (WDI): Fertility rate, total

Comparable country series used widely in development analysis.
data.worldbank.org/indicator/SP.DYN.TFRT.IN
Our World in Data — Fertility rate

Long-run visualisations and metadata built from UN/WB series.
ourworldindata.org/fertility-rate
IHME (HealthData) — Global fertility forecasts (The Lancet, 2024)

Research-grade projections and scenario framing through 2100.
healthdata.org/.../lancet-dramatic-declines...
INSEE (France) — Latest demographic report

National statistical release with France’s most recent fertility updates.
insee.fr/en/statistiques/8726555
Statistics Korea / vital statistics (South Korea fertility)

National reporting on record-low fertility; press-facing summaries often cite the official releases.
kostat.go.kr/anse/
CIA — The World Factbook: Total fertility rate

Country profile cross-checks and contextual indicators.
cia.gov/the-world-factbook/