Global Fertility Rates in 2025: A Comprehensive Overview
Global Fertility Rates in 2025
Fertility is one of the strongest drivers of long-term population size and age structure. This page summarises Total Fertility Rate (TFR) and Crude Birth Rate (CBR) using the latest international demographic frameworks (UN World Population Prospects) and widely used statistical repositories for cross-checks.
≈ 2.1
Around this level, a population tends to replace itself in the long run (without migration).
~2.2–2.4
Global averages differ slightly by source and modelling choices; use the same series when comparing.
Aging vs. youth bulges
Low fertility accelerates aging; high fertility increases the share of children and youth.
Schools · jobs · pensions
Fertility shifts planning needs across education, labour markets, healthcare, and pension systems.
What TFR and CBR measure
Total Fertility Rate (TFR) estimates the average number of children a woman would have over her lifetime if age-specific fertility rates observed in a given year persisted. Crude Birth Rate (CBR) counts annual births per 1,000 people and is sensitive to the age structure (countries with younger populations can have higher CBR even at similar TFR).
Top 10 countries by Total Fertility Rate (2025)
The table below reproduces a compact “Top 10” snapshot (TFR + CBR). In practice, rankings can move slightly depending on the exact WPP revision and whether the series is estimates vs. projections.
| Rank | Country | TFR (children/woman) | CBR (births/1,000) |
|---|---|---|---|
| 1 | Niger | 6.7 | 45.8 |
| 2 | Angola | 5.9 | 42.3 |
| 3 | Somalia | 5.8 | 41.5 |
| 4 | DR Congo | 5.7 | 40.8 |
| 5 | Mali | 5.6 | 39.7 |
| 6 | Chad | 5.5 | 38.9 |
| 7 | Burundi | 5.4 | 37.6 |
| 8 | Nigeria | 5.2 | 36.8 |
| 9 | Uganda | 5.0 | 35.4 |
| 10 | Benin | 4.9 | 34.7 |
Chart: TFR in the 10 highest-fertility countries (2025)
Bottom 10 countries by Total Fertility Rate (2025)
Very low fertility usually reflects delayed family formation, high housing/childcare costs, intensive work cultures, and fast educational expansion. These countries often face rapid aging and shrinking cohorts entering the workforce.
| Rank | Country | TFR (children/woman) | CBR (births/1,000) |
|---|---|---|---|
| 1 | South Korea | 0.7 | 5.9 |
| 2 | Singapore | 0.9 | 6.8 |
| 3 | China | 1.1 | 8.5 |
| 4 | Italy | 1.2 | 7.6 |
| 5 | Japan | 1.2 | 7.2 |
| 6 | Spain | 1.2 | 7.4 |
| 7 | Malta | 1.3 | 8.0 |
| 8 | Portugal | 1.3 | 8.2 |
| 9 | Greece | 1.3 | 8.4 |
| 10 | Poland | 1.4 | 8.9 |
Chart: TFR in the 10 lowest-fertility countries (2025)
Regional patterns and what drives them
The global picture is highly uneven. Broad regional differences tend to track: child survival, access to contraception, female education and labour participation, urbanisation, housing affordability, and social norms around timing of marriage and parenthood.
Sub-Saharan Africa: highest fertility, fastest cohort growth
High TFR remains concentrated in parts of Sub-Saharan Africa, reinforcing a youthful age structure and rapid expansion of school-age cohorts. This raises near-term needs for education, health systems, and job creation at scale.
- Higher desired family size and earlier childbearing in many settings
- Uneven access to modern contraception and reproductive health services
- Population momentum: a large share of women entering childbearing ages
East Asia: extremely low fertility and accelerated aging
Several East Asian countries remain below 1.5 children per woman, reflecting delayed family formation, high living costs, and strong work-family trade-offs. The result is shrinking cohorts entering the labour market and rising old-age dependency.
- High housing and childcare costs relative to household income
- Late marriage/partnership formation, fewer births at younger ages
- Policy focus: childcare, housing, parental leave, and workplace flexibility
Europe: persistent below-replacement fertility
Many European countries remain below replacement level, with variation driven by family policy design, childcare availability, gender norms, and labour market security. Immigration often becomes a key factor shaping workforce size where fertility is low.
- Delayed parenthood and fewer second/third births
- Large regional differences inside the EU
- Long-run impact: aging and fiscal pressure on pensions and healthcare
Why fertility trends matter
Fertility changes reshape population structure with a lag: children born (or not born) today become students in a few years, workers in two decades, and retirees in half a century. That lag is why fertility is both “slow-moving” and strategically important.
Insights and interpretation (2025 context)
- Low-fertility countries tend to face faster aging, fewer labour-market entrants, and higher fiscal pressure on pensions and healthcare. Policy levers often focus on childcare, housing, parental leave, and work-family compatibility.
- High-fertility countries often experience rapid growth of child and youth cohorts, requiring large investments in schools, maternal/child health, and job creation. Even when fertility begins to decline, population momentum can keep growth high for decades.
- Migration becomes more pivotal where fertility is below replacement. It can stabilise workforce size, but it does not automatically solve population aging without broader productivity and labour-force participation gains.
- CBR can be misleading alone: a youthful country can have a high birth rate per 1,000 people even if TFR is already falling, simply because many women are in childbearing ages.
Methodology (how the ranking is built)
Indicator definitions: TFR is expressed as children per woman; CBR is births per 1,000 population. For cross-country comparisons at a single point in time, the preferred practice is to use one harmonised international dataset.
- Primary backbone: UN World Population Prospects (WPP) revision for fertility concepts, country coverage, and projection framework.
- Cross-checks: World Bank indicator pages are useful for harmonised historical series where available; Eurostat is used for EU-specific definitions and notes.
- Rounding: values are typically rounded to one decimal for readability in Top-10 snapshots; small differences can reorder ranks in close clusters.
- Limitations: projections depend on modelling assumptions; abrupt policy shifts, economic shocks, conflicts, and migration changes can move real outcomes away from the central path.
FAQ
Replacement is slightly above 2.0 because some children do not survive to adulthood and because of sex ratio dynamics. The exact replacement level varies by mortality patterns.
Yes. If many women are entering childbearing ages (a youthful age structure), the number of births can rise even while births per woman (TFR) declines.
TFR is usually better for comparing “family size” patterns across countries because it is less distorted by age structure. CBR is still useful, but interpret it together with the population’s age distribution.
Common contributors include delayed partnership and parenthood, high housing/childcare costs, job insecurity for young adults, and workplace norms that make combining careers and children difficult.
Some measures (affordable childcare, paid leave, housing support) can improve conditions for having children, but impacts differ by context and often take years. Short-term bonuses rarely change long-run trends on their own.
Whenever a new WPP revision is released or when a primary statistical series updates the latest year. For consistency, keep historical comparisons within the same revision/series.
