<p>Iron ore plays an important role in the country’s economic and infrastructure development, but the exploration and demarcation of the resource remain challenging and costly. Therefore, the current study aims to map potential iron ore-bearing zones using satellite data in mineral-rich regions of Odisha and Jharkhand, India. The study demonstrates two approaches [band ratio and principal component analysis (PCA)] using multi-spectral data of the Landsat-5 sensor for the detection and delineation of iron ore-bearing zones. Moreover, the associations of iron ore occurrences with different geological features are also demonstrated. The iron ore-bearing zones predicted by various approaches were validated using the explored and exposed iron ore deposits. The study examined different combinations of band ratios for distinguishing iron ore-bearing zones from other objects based on spectral characteristics. It was observed that three band ratios [Red (Band 3)/Blue (Band 1), SWIR 1 (Band 5)/NIR (Band 4), and SWIR 2 (Band 7)/ NIR (Band 4)] of the Landsat-5 sensor offer good results to detect iron ore bearing zones. The results were further compared with the PCA-based results for comparative evaluations of the two approaches. It was observed from the PCA analysis using all the band data fail to provide unequivocal results to separate the iron ore bearing zones in any of the PC layers, and thus, a selective PCA was used with four bands (Band 1, Band 3, Band 4, and Band 5) of the Landsat-5 sensor. The comparative results indicated that PCA-based results (PC4 layer) offer better delineations in comparison to all the band ratios. The results further revealed that occurrences of iron ores are closely associated with certain geological features and alteration characteristics. The study results can be useful in the strategic exploration of iron-bearing zones for further confirmation of the deposit with reduced cost and time.</p>