In previous studies on power-distribution equipment systems in Senegal, researchers have explored their impact on rural electrification and cost-effectiveness. This study employs multilevel regression models, including fixed effects and random effects, to analyse data from power-distribution systems across different regions of Senegal. The multilevel regression analysis revealed a significant positive correlation between the number of households served and the cost-effectiveness index (CEI) with a coefficient estimate of 0.85 and a 95% confidence interval of [0.72, 0.98]. The replication study confirms the effectiveness of multilevel regression analysis in evaluating power-distribution systems' cost-effectiveness. Future research should consider incorporating additional variables to enhance the robustness and accuracy of cost-effectiveness measurements. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.