Based on the data collected by Inter-American Tropical Tuna Commission (IATTC) from 2015 to 2017 and the matched satellite remote sensing data, a two-stage boosted regression tree(BRT) model was built to model the habitat of bigeye tuna free-swimming schools in the eastern Pacific Ocean and explore its temporal and spatial distribution pattern. The results showed that, compared to environmental factors, spatial factors had a greater impact on the abundance of bigeye tuna free-swimming schools. In terms of environmental factors, latitude, longitude, mixed layer depth, month, and sea surface temperature are the main influential factors that affect the fishing success rate of bigeye tuna free-swimming schools, while the main factors affecting the abundance of bigeye tuna free-swimming schools are longitude and sea surface chlorophyll-a concentration. Bigeye tuna is mainly located in the sea area south of 10°S and west of 95°W. From July to September in 2016 and Febuary to April in 2017, the spatial distribution predicted by the two-stage BRT model showed that some highly dense tuna free-swimming schools inhabited the equatorial waters with longitude of 150°W and latitude of 0° and waters with longitude of 120°W and latitude of 10°S, respectively. With respect to temporal trend, the inter-annual variation of the monthly average of the abundance of bigeye tuna is small, but the monthly difference is large. The monthly variation revealed that the highest value occurred in July and then dropped to the lowest value in August. The results of this study can provide reference for conservation and management of tuna resources in the EPO.