Top 100 Countries by Commercial Vehicle Fleet Size, 2025

by admin December 17, 2025 988 12 min read

This page ranks countries by the size of their commercial vehicle (CV) fleet and provides two complementary views: (1) total commercial vehicles in use (fleet size, absolute) and (2) commercial vehicles per 1,000 people (fleet intensity). The goal is not just to list “who is #1”, but to explain why the ranking looks the way it does and what it implies for logistics capacity, road wear, fuel demand, and economic structure.

Quick snapshot (computed from the embedded Top-100 dataset)

Global Top-100 total: — commercial vehicles (in-use stock, in thousands).
Concentration: Top-10 countries hold — of the Top-100 total; Top-20 hold —.
Interpretation tip: absolute fleet size tracks economic scale, while per-capita fleet size tracks transport intensity, geography, and specialization.

What is measured here

Commercial vehicles in use is the stock of vehicles on the road that are primarily used for commercial and freight/passenger operations (e.g., trucks and buses, depending on national reporting conventions). In cross-country comparisons, “in-use” stock is generally more stable than “new registrations” because it reflects accumulated fleet, scrappage, and replacement cycles.

Data year and comparability

This “2025 edition” uses a single, harmonized snapshot year (2019) for the Top-100 list to avoid mixing partially reported or methodologically inconsistent years. Many countries publish fleet data with different lags; a single year is the cleanest way to compare levels across countries.

How to read the two rankings

1) Absolute fleet size highlights countries where road-based commerce is huge in total volume (large internal markets, large territories, major manufacturing/logistics hubs).
2) Fleet per 1,000 people highlights countries where commercial mobility is intense relative to population (high-income logistics ecosystems, dispersed settlement patterns, transit-heavy economies, or structural reliance on road transport). It can also be elevated in smaller countries if the economy is highly trade/logistics oriented.

Note on per-capita calculations: to keep all data inside the page (no external API calls), the per-capita ranking is computed from the embedded CV stock (thousand vehicles) and embedded population estimates (million people). This yields CV per 1,000 people = CV_thousand / Population_million.

Rankings and distribution

The absolute fleet ranking tends to be dominated by the largest economies and territories, because even “average intensity” multiplied by a huge population and a huge internal market produces a very large stock. Per-capita ranking flips the lens: it highlights countries where commercial mobility is intense relative to population, which can reflect higher income, longer supply chains, heavier reliance on road freight, or specialization in trade/logistics.

Table 1 — Top 100 countries by commercial vehicles in use (stock)

Units are shown as thousand vehicles for readability (e.g., “150,000 thousand” ≈ 150 million). Year: 2019.

Rank	Country	CV in use (thousand; 2019)

Bar chart — Top 20 by absolute fleet size

Reading tip: the distribution is highly concentrated. A small set of very large economies accounts for most of the Top-100 fleet stock.

Table 2 — Top 100 countries by commercial vehicles per 1,000 people

Computed inside the page as CV per 1,000 people = CV_thousand / Population_million. This makes the per-capita ranking reproducible without external API calls.

Rank	Country	CV per 1,000 people (2019)

Bar chart — Top 20 by per-capita fleet size

Why per-capita differs: some smaller or highly logistics-oriented economies can rank much higher on intensity than on absolute volume, even if their total fleet is modest.

FAQ (practical interpretation)

1) Does a larger CV fleet mean “better logistics”?
Not automatically. A large fleet can reflect a large internal market, but also older vehicles staying longer in service, or policy/price signals that slow replacement. For performance, you’d also look at fleet age, utilization, road freight ton-km, and infrastructure quality.

2) Why can per-capita CV numbers look surprisingly high in some countries?
Per-capita is sensitive to (a) population size, (b) settlement dispersion, (c) trade intensity, and (d) the balance between rail, road, and waterways. Countries with strong road-based commerce and smaller populations can appear “fleet-dense” even if their absolute fleet is far below the largest economies.

3) Can this ranking be used for market sizing?
Yes—cautiously. Fleet stock is a strong input for aftermarket demand (maintenance, tires, spare parts), but you’ll still want segmentation by vehicle class (light commercial vs heavy trucks vs buses) and by duty cycle.

Regional structure and source transparency

Country rankings are useful, but regional aggregation adds context. It helps separate: (a) “scale effects” (large economies naturally accumulate large fleets) from (b) “structure effects” (trade intensity, geography, and reliance on road freight). The tables below are computed only from the embedded Top-100 dataset used in this page.

Table 3 — Regional totals and share of the Top-100 fleet

Totals are computed from the embedded Top-100 “commercial vehicles in use” values (thousand units, 2019). Shares sum to 100% of the Top-100 total (this is not a full-world total).

Region	CV total (thousand; 2019)	Share of Top-100

Chart — Regional share of the Top-100 fleet

Interpretation note: regions can look “large” either because they contain very large domestic markets, or because several medium/large economies cluster together. To compare transport intensity, use the per-capita ranking (computed using World Bank population totals).

Method notes (what’s primary vs derived)

Primary metric (fleet stock): “Commercial vehicles in use” (stock) by country and year (2005–2019), published by OICA.
Derived metric (per-capita): CV per 1,000 people is calculated in-page as CV_thousand / Population_million using World Bank “Population, total”.
Why this matters: keeping the primary data and the derivation rules explicit makes the ranking reproducible and auditable.

Primary sources (with direct links)

OICA — Commercial Vehicles: Vehicles in use (Excel)
The underlying “stock” time series used for the Top-100 fleet size table (2005–2019, thousand units; noted as estimated figures in the file).
https://www.oica.net/wp-content/uploads/CV_Vehicles-in-use.xlsx
OICA — Statistics / usage notes (site info & FAQ)
Reference point for how OICA publishes statistics and general usage notes (e.g., frequency and “free for non-commercial use” guidance).
https://oica.net/
NationMaster — “Commercial vehicles in use” indicator page (secondary mirror of OICA)
Useful as a cross-check/quick UI for ranking by year; it explicitly attributes the indicator source to OICA.
https://www.nationmaster.com/nmx/ranking/commercial-vehicles-in-use
World Bank — Population, total (SP.POP.TOTL)
Used to compute CV per 1,000 people inside this page (population totals by country and year).
https://data.worldbank.org/indicator/SP.POP.TOTL