The provision of reliable power distribution equipment in Senegal is crucial for economic development but often expensive. Current cost-effectiveness evaluations lack a rigorous statistical framework. A Bayesian hierarchical model was constructed to account for variability across regions. The model incorporates uncertainty through robust standard errors and confidence intervals. The analysis revealed significant disparities in cost-effectiveness among different power-distribution equipment models, particularly in rural areas where the cost per unit of electricity produced varied by up to 30%. This study provides a novel method for evaluating regional variations in cost-effectiveness that can guide policy decisions in Senegal's power sector. Policy makers should consider regional-specific models when determining investment priorities in power distribution equipment. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.