The adoption rates of transport maintenance depots systems in Rwanda have been monitored over several years, with limited empirical data available to assess their effectiveness. A time-series forecasting model was developed to analyse adoption trends within the Rwanda context, incorporating relevant historical data for validation. The forecasting model indicated an upward trend in adoption rates over the study period, with a predicted increase of approximately 20% by . The time-series forecasting model provided valuable insights into future trends and could serve as a predictive tool for policymakers aiming to enhance depot systems effectiveness. Policymakers should consider the forecasted adoption rates in planning future investment and capacity expansion within Rwanda’s transport maintenance depots. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.