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Schistosomiasis is a parasitic infection caused by Schistosoma japonicum. It remains a principal local health issue in the Philippines, demonstrating endemicity in 28 provinces and afflicting thousands of Filipino individuals annually. Despite this, no clear distribution maps for the disease have been comprehensively reported. Therefore, species distribution modeling (SDM) employing the MaxEnt algorithm and GIS application techniques was utilized to denote the potential risk of schistosomiasis in the country. With a high AUC score of 0.846, the SDM yielded a favorable and reliable correlative map illustrating a predicted schistosomal temporal distribution concentrated primarily on the country's eastern portion with a more pronounced wet than dry season. The precipitation of the driest quarter was determined to be the most significant contributing factor among the bioclimatic variables evaluated. This suggests a possible increase in adaptations concerning the rainfall and thermal tolerances of the parasites' vectors. Moreover, socioeconomic status between Philippine regions revealed an inverse proportion with the number of schistosomiasis cases. This study also discussed the potential role of climate change on the range shifts and the potential risk of parasite infection in the Philippines. [Display omitted] • High-risk areas of schistosomiasis were predicted in the eastern Philippines. • Precipitation of the driest quarter is the most influential bioclimatic predictor. • GIS application can be used for policy creation of mitigating schistosomiasis. • Model reveals areas with the same condition for recorded schistosome occurrence. [ABSTRACT FROM AUTHOR]