This paper develops a mathematical model to predict motor vehicle ownership based on household (HH) characteristics. The model is tested using household visit surveys in the Western Province of Sri Lanka (CoMTrans, 2014). The province which has the country's highest population density (1,600/km 2 ) and road density (0.9 km/km 2 ) as well as a motor vehicle ownership of 206 vehicles per 1,000 people. The modelling is disaggregated into motorcycles, three-wheelers, vans, and cars (including jeeps and pick-ups). The motor vehicle fleet comprises 51% motorcycles, 20.2% threewheelers, 6.7% vans, and 17.7% cars apart from commercial vehicles. The purchasing cost of motor vehicles in Sri Lanka varies widely due to different taxes imposed at importation. A binary logistic regression with cross-validation statistical theories was used to predict the HH ownership of different vehicles, based on an income-based testing scenario for determining a HH's likelihood of owning a particular type of vehicle.Motorcycles, three-wheelers, vans, and cars listed in ascending order of cost of ownership and operation were tested against the characteristics of 35,850 HHs using R, a software analytical tool. The analysis found that private vehicle ownership depends on attributes of a HH, such as its size, average monthly income, and the percentage of workers, school and kindergarten children, and males in that HH.