This study focuses on methodological evaluation of manufacturing systems in Ugandan plants to reduce operational risks through time-series forecasting models. A theoretical framework will be developed based on existing literature and empirical observations, incorporating statistical models such as ARIMA (AutoRegressive Integrated Moving Average) to forecast future trends in operational risks within Ugandan manufacturing plants. This theoretical framework provides a robust method for assessing and managing operational risks in Ugandan manufacturing plants using advanced statistical techniques. Manufacturing companies should consider implementing these models to enhance their risk management strategies, leading to improved operational efficiency and cost savings. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.