Indonesia, the world’s largest tuna producer, contributed 17% (1.12 million metric tons) to global tuna production in 2016. Mapping fisheries potential in Indonesia’s vast waters presents challenges, but remote sensing technology enables effective analysis of oceanographic parameters. This study uses Multiple Linear Regression, Correlation Analysis, and T-Tests to examine the relationship between chlorophyll-a, sea surface temperature (SST), and depth with tuna catches. Results show a strong correlation for bigeye tuna, while frigate, skipjack, yellowfin, and mackerel-tunas-bonitos exhibit strong relationships. Longtail tuna shows a weak correlation. F-tests indicate that oceanographic parameters significantly affect the catches of bigeye, frigate, skipjack, yellowfin, and mackerel-tunas-bonitos, but not longtail tuna. T-tests reveal that chlorophyll-a and depth influence frigate and mackerel-tunas-bonitos, while depth alone impacts bigeye, skipjack, and yellowfin tuna. No oceanographic parameters significantly affect longtail tuna. The most productive fishing areas are in Eastern waters for bigeye, frigate, and longtail tuna and in Indian waters for skipjack and yellowfin tuna. Central waters show the highest potential for mackerel-tunas-bonitos.