Municipal water systems in Nigerian cities often face challenges related to reliability due to factors such as aging infrastructure, supply disruptions, and inadequate maintenance. The proposed methodology will utilise Bayesian statistical techniques to account for spatial heterogeneity and temporal variations in water supply systems. The model will incorporate data from multiple sources including government records, community feedback surveys, and automated meter reading (AMR). The Bayesian hierarchical model provides a robust framework for assessing and improving municipal water system performance in Nigeria, offering insights into areas needing targeted interventions. Policy recommendations include prioritising infrastructure upgrades in high-failure-rate regions, enhancing community engagement to improve AMR data quality, and implementing regular maintenance schedules based on model predictions. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.