Tuberculosis (TB) remains one of the 21st century's crucial public health problems. Today, it is the second leading cause of death from a single infectious disease agent. Spatial information on health-related diseases like TB is not well documented in Nigeria. The study of Spatial Distribution of TB in Niger State is necessitated for broad and more comprehensive coverage of TB cases within the State. As such, there is a need to carry out a spatial auto-correlation analysis of the entire 25 Local Government Areas (LGAs) of the State to explore the epidemiological data, distribution, and pattern of infection from 2016 to 2020. This study investigated the spatial auto-correlation structure with the Moran Index, Anselin's local Moran's I, Getis-ord local statistics and kriging interpolation methods. The result of the Analysis of Variance (ANOVA) showed that there was a significant difference in infection patterns between LGAs. This result implied variability in the number of cases across different local governments within the study periods. Although the considerable number of TB-reported instances, the analysis based on Moran's I and global G revealed no clustering pattern in the data. The local indicator of spatial association result showed that the number of cases was random across the LGAs; there were no significant clusters. Kriging interpolation method identified Kontogora, Bosso and Chanchaga LGAs as hotspots of TB cases in Niger State. This study provides information that can assist policymakers in rationally planning targeted interventions to effectively control TB while addressing the underlying socio-economic risk factors in Niger State. This study has shown that despite data limitations, Geostatistical approaches are viable for understanding interpolation patterns.