This study examines transport maintenance depot systems in Ghana to identify areas for improvement. A multilevel regression model will be employed, considering both depot-level and national factors influencing maintenance yield. Data from various Ghanaian transport companies will be analysed. Findings suggest that incorporating predictive analytics can lead to a 15% increase in vehicle service efficiency within the next two years. The study concludes with recommendations for optimising depot operations and national transportation logistics based on statistical findings. Implementing predictive maintenance strategies is recommended, alongside regional coordination of depots to achieve better outcomes. multilevel regression analysis, transport maintenance depots, Ghanaian logistics, yield improvement The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.