Yellowfin tuna (Thunnus obesus) is one of the most important and most caught fish in the eastern Indian Ocean off west Sumatera and has extensive migration. To develop an appropriate prediction model and to understand the contribution of oceanographic parameters in the potential habitat of Yellowfin tuna, remotely sensed data and habitat modeling were used. Daily data of sea-surface temperature (SST), sea-surface salinity (SSS) and sea-surface height (SSH) were downloaded from the marine copernicus website, meanwhile fishing vessel position for Yellowfin tuna were obtained from fishing port Samudera, Bungus, west Sumatera, from January through December 2015. Daily fishing vessel position and environmental parameters were used for maximum entropy model construction. The model predictive performance was then evaluated using a threshold-independent metric, the area under the curve (AUC) metric of the receiver operating characteristic (ROC). Maximum entropy model results (AUC > 0.90) indicated its potential to figure out the spatial distribution of Yellowfin tuna. In general, SST (50.5%) is the most affective variable in the Yellowfin tuna distribution, followed by SSS (37%) and SSH (12.5%). This study showed that integration multi remotely sensed data and a modeling approach provide an innovative way to decide the potential fishing zones of the Yellowfin tuna in the eastern Indian Ocean off west Sumatera.