This study examined the relationship between revenue collection and service delivery in Kisoro District, Uganda, using statistical models, including regression and Pearson correlation analysis. Regression analysis results revealed that funding adequacy and infrastructure quality had negligible statistical significance in explaining variations in service delivery (p > 0.05). Similarly, revenue collected and infrastructure quality also showed no significant effects on service delivery outcomes (p > 0.05). The Pearson correlation analysis revealed a strong and statistically significant positive relationship between revenue and service delivery, with a correlation coefficient of 0.745 and a p-value of 0.000. The study concluded that while revenue collection correlates strongly with service delivery, other unmeasured factors likely contribute to variations in service outcomes. It identified limitations in data precision and methodological approaches, such as the broad confidence intervals and high standard errors, which underscored the need for more comprehensive data and robust analytical models. Key recommendations included improving revenue collection mechanisms through digital systems, expanding the revenue base, and enhancing taxpayer awareness. Additionally, the study advocated for better resource allocation prioritizing critical service areas, strengthening governance and accountability systems, and investing in high-quality infrastructure. Further research was recommended to explore the causal relationships between revenue collection and service delivery and incorporate broader contextual factors like governance and human resources.