This study applies remote sensing (RS) as a geologic mapping aid tool , using Handeni Block of Tanzania as a case study. To achieve the objective of this study, we have utilized various RS processing and image enhancement techniques on multispectral data, including ASTER, Landsat 5, Landsat 8, and Sentinel 2A. The method proved successful whereby both Landsat-5-data with band combination (BC) 7:4:2 and 7:5:4 and band ratio (BR) 5/3:5/1:7/5 and Landsat-8 data with BCs 5:6:7 and 7:6:4 mapped out marble units. Sentinel 2A data (with BC 8:11:3, BRs 12/2:11/2:8/11; 12/4:11/3:11/2 and 12/4:12/2:11/3) together with image enhancement decorrelation stretch on BC 4:3:2 and BC 8:11:3 images succeeded to map other major geologic units. The findings were tested using another approach, an unsupervised classification (K-means algorithm) of Landsat 8 data and unsupervised and supervised classifications by IsoData and minimum distance algorithms, respectively. Similar results were obtained from the image classification whereby Sentinel 2A data produced classified images, which consistently delineate the same lithologies. Geologic structures (lineaments) have been mapped by ASTER DEM data. The result from supervised classification using end-member spectra of the collected representative rock samples also supports the remotely sensed lithologies, demonstrating the usefulness of RS in geologic mapping. The finding of this work have shown that the integration of RS and rock spectral analyses can be used as a robust aiding tool in geologic mapping. The method is more resource efficient than a purely conventional approach.