Off-grid community systems in Senegal are increasingly important for ensuring reliable access to electricity without reliance on traditional grid infrastructure. The study employs a combination of data analysis techniques including time-series forecasting models such as ARIMA (AutoRegressive Integrated Moving Average) to evaluate system performance in Senegal's agricultural sector. A significant proportion—over 75%—of the off-grid systems showed stable annual growth trends, indicating their reliability over a five-year period. The ARIMA model accurately predicted these trends with an uncertainty of ±20%. This finding is crucial for policy makers in planning future investments and expansions. The integration of time-series forecasting models has provided valuable insights into the operational stability of off-grid systems, contributing to more informed decision-making processes. Further research should focus on expanding model validation across different regions within Senegal and exploring longer-term reliability impacts. Off-Grid Systems, Time-Series Forecasting, ARIMA, Reliability Measurement, Senegal Agriculture The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.