Industrial machinery fleets play a critical role in Rwanda's manufacturing sector, contributing to economic growth and productivity. A mixed-methods approach was employed, combining data from fleet management software logs with structured interviews to assess fleet systems' reliability. The study adopted a pre-post intervention design with baseline measurements taken before implementation of the quasi-experimental treatment. The analysis revealed that an average uptime rate of 85% for machinery fleets in Rwanda was achieved, with maintenance costs reducing by approximately 10% post-intervention. This study provides evidence on the effectiveness of industrial machinery fleet management systems in Rwanda and highlights areas for future improvement. Further research should explore the long-term impact of these systems and investigate potential cost savings through improved maintenance strategies. Industrial Machinery Fleets, Reliability Assessment, Quasi-Experimental Design, Manufacturing Sector, Rwanda The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.