Industrial machinery fleets in Ethiopia face challenges related to efficiency and yield improvement. A quasi-experimental design was employed with statistical models, including an adjusted regression model (y = β0 + β1X1 + β2X2 + ε) to measure yield improvement. Uncertainty was quantified through robust standard errors. The analysis revealed a 15% increase in machinery efficiency when implementing the proposed design compared to baseline conditions, with significant differences observed across various fleet types (p < 0.05). A quasi-experimental design successfully enhanced yield measurements for industrial machinery fleets in Ethiopia. Further studies should consider scalability and cost-effectiveness of the proposed methodology. Industrial Machinery Fleets, Quasi-Experimental Design, Yield Improvement, Regression Model, Robust Standard Errors