Recent advancements in process-control systems have sparked interest in their potential to enhance agricultural productivity, particularly in resource-limited settings such as Uganda. However, empirical evaluations of these systems' efficacy are scarce and often lack rigorous methodological frameworks. A comprehensive Randomized Controlled Trial (RCT) design was employed, with two treatment groups receiving different process-control interventions and one control group. Data collection included pre- and post-intervention yield measurements, soil quality assessments, and farmer satisfaction surveys. Statistical analyses used a linear regression model to estimate the impact of intervention on yields. The preliminary findings suggest that process-control systems can lead to significant increases in crop yields by up to 20% compared to control groups, with a confidence interval ranging from 15-25%, indicating robust statistical support for positive effects. This study provides evidence supporting the use of process-control systems as a viable strategy for improving agricultural productivity in Uganda. The results highlight the importance of rigorous methodological approaches in evaluating such interventions. The findings from this study should inform future RCT designs and policy recommendations aimed at integrating advanced technologies into Ugandan agriculture to achieve sustainable yield improvements. Agricultural productivity, process-control systems, Randomized Controlled Trial (RCT), crop yields, Uganda The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.