Industrial machinery fleets are crucial for Rwanda's economic development, yet their adoption rates have been inconsistent. A quasi-experimental design was employed, incorporating surveys and observational data collection methods. Statistical models were used for analysis, including logistic regression with robust standard errors. The survey revealed that a significant proportion (65%) of machinery systems in Rwanda have been adopted within the past year, with higher adoption rates observed among larger enterprises. Quasi-experimental designs provide valuable insights into the adoption dynamics of industrial machinery fleets in Rwanda, offering robust methods for future studies. Further research should focus on understanding the specific factors that drive adoption and explore potential barriers to full implementation. industrial machinery, fleet management, adoption measurement, quasi-experimental design The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.