This study focuses on evaluating field research stations in Nigeria for forecasting adoption rates related to energy policies. Field research stations were analysed through systematic data collection methods, including surveys and statistical modelling. A linear regression equation was employed to forecast adoption rates over time with robust standard errors accounting for potential measurement uncertainties. The analysis revealed a significant positive correlation between investment levels in renewable energy sources and the rate of adoption (p < 0.05). Field research stations demonstrated effectiveness in data collection, but further validation is needed to ensure model reliability across different regions in Nigeria. Continuous monitoring and periodic recalibration of the forecasting models are recommended based on ongoing energy policy changes and technological advancements. Field Research Stations, Time-Series Forecasting, Adoption Rates, Renewable Energy, Linear Regression The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.