Community health centers in Uganda face challenges in delivering consistent clinical outcomes due to variability in service delivery. A comprehensive meta-analysis was conducted, incorporating data from multiple studies on community health centers in Uganda. Time-series forecasting models were applied to predict and analyse clinical outcomes over a period of at least one year. The analysis revealed an average forecast accuracy rate of 75% for future clinical outcome assessments using the proposed time-series model, with confidence intervals indicating robust standard error values. This study highlights the potential of time-series forecasting models in enhancing clinical outcome assessment within community health centers in Uganda. Further research should focus on validating these findings through randomized controlled trials and exploring integration of machine learning algorithms for improved prediction accuracy. Community Health Centers, Time-Series Forecasting, Clinical Outcomes, Meta-Analysis, Uganda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.