Field research stations in Nigeria have been established to support agricultural development, but their operational efficiency is not well understood. A Bayesian hierarchical model was applied to analyse data from multiple research stations. The model accounts for variability at different levels (e.g., station-specific effects, regional differences) by incorporating prior knowledge into the analysis. The analysis revealed that efficiency gains varied significantly across stations and regions, with some stations showing substantial improvements in productivity when resource management was optimised. This study provides a robust framework for evaluating and enhancing field research station systems in Nigeria, offering insights that can guide future policy decisions aimed at improving agricultural productivity. Policy makers should prioritise the implementation of best practices identified through this analysis to maximise the impact of resources allocated to research stations. Bayesian hierarchical model, field research stations, efficiency gains, resource allocation, Nigeria The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.