Background Road traffic accidents claim over 1.3 million lives annually around the globe and remain a key socio-economic challenge today. At 20.1 per 100 000, Botswana's fatality rate is higher than the global average of 17.4. Previous studies on the causes of road crashes in Botswana have not explored statistical causality. This study is thus grounded on the theory of causality. Objectives This study sought to determine the causes of road traffic accidents and fatalities in Botswana. For this purpose, the article discusses the accident count model based on Botswana data. Method The study used road accident data from 2008 to 2017. Econometric modelling on Gretl was used to compute two ordinary least squares (OLS) regression models. Manual elimination of insignificant variables was performed through the iterations. Results Both models are statistically significant at p ≤ 0.001, but the accident count model, with an adjusted R[sup.2] value of 0.99 against 0.83, is more robust and has a better predictive power as opposed to the fatalities model. At the individual variable level, the analysis shows mixed results. Conclusion The study contends that increased exposure and night-time travel increase road crashes, whilst expansion of road infrastructure is inversely related to road accidents. An increase in both population density and exposure leads to increased fatalities. Regulating the importation of used vehicles and investment in rail transport is a potential policy panacea for developing economies. Future studies should investigate the causes of pedestrian fatalities and night accidents.