The study investigated the relationship between data management and the efficiency of immigration stock and flow management within Uganda’s National Citizenship and Immigration Control (NCIC). A descriptive and correlational research design was employed, using both quantitative and qualitative approaches. Data were collected from a sample of 293 respondents drawn from different departments and regional offices of the Directorate of Citizenship and Immigration Control (DCIC). Questionnaires and interviews were used to gather information on data management practices and operational efficiency. The collected data were analyzed using the Statistical Package for Social Sciences (SPSS) version 25, employing descriptive statistics, Pearson’s correlation, and regression analysis. The analysis revealed a strong positive correlation between data management and immigration service efficiency, with a Pearson correlation coefficient (r = 0.775, p = 0.000), indicating that improvements in data management were strongly associated with enhancements in immigration services. The results suggested that as the NCIC improved data accuracy, regular updating, and integration across its systems, the timeliness, responsiveness, and overall quality of immigration service delivery also increased. The significance value of p = 0.000, being less than the 0.05 threshold, confirmed that this relationship was statistically significant. Therefore, the null hypothesis, which stated that there was no significant relationship between data management and immigration efficiency, was rejected.The study concluded that effective data management is a critical determinant of efficiency in immigration stock and flow management. It enhances operational performance by reducing processing delays, improving decision-making, and facilitating the tracking and verification of immigration documents. The findings further demonstrated that data integration and accessibility are key to ensuring reliable service delivery and institutional accountability within NCIC operations. It was recommended that the Directorate should strengthen its data governance frameworks, invest in continuous staff training on digital data systems, and enhance the interoperability of its databases with other government institutions such as NIRA and URA. Strengthening these practices would ensure timely data sharing, minimize duplication, and improve the efficiency of immigration services in Uganda.