This study examines industrial machinery fleets in Ethiopia, focusing on adoption rates of new technologies. A Difference-in-Differences (DID) model was employed, with pre- and post-policy intervention data from a sample of industrial machinery fleets across Ethiopia's manufacturing sectors as the basis for analysis. The DID model revealed an adoption rate of new machinery increased by approximately 25% in the post-intervention period compared to the control group. The DID model was found effective in measuring adoption rates, with significant improvements observed post-policy intervention. Further research should explore DID's robustness across different sectors and interventions. Difference-in-Differences, Adoption Rate, Industrial Machinery, Ethiopia The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.