Rwanda’s transport sector is a critical component of its economy, with maintenance depots playing a pivotal role in ensuring vehicle reliability and safety. Panel data techniques were employed to analyse the impact of various factors on maintenance efficiency, focusing on depots across Rwanda’s key sectors. The analysis revealed a significant reduction in vehicle downtime attributed to improved predictive maintenance practices. This study provides empirical evidence supporting the effectiveness of structured maintenance strategies in reducing operational risks for transport systems. Further research should explore scalability and cost-effectiveness implications of these findings across broader geographical regions. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.