Overwhelming anthropogenic activities combined with the effects of climate change pose extreme threats to wildlife resources, resulting in habitat loss and the decline of many mammal species. The African elephant (Loxodonta africana) is an endangered large mammal occurring in some protected areas in Africa. In this study, a species distribution model using the spatial maximum entropy algorithm was developed to determine the geographic extent and distribution of the elephant in Omo National Park. Elephant surveys were conducted in the wet and dry seasons in 2021 and 2022. Occurrence data and the 12 predictor variables were processed and framed, and the corresponding models were built for two seasons separately in the Geographic Information System and R software. The modeled seasonal combined results of the elephant range have a total area of 1999 km2 (39% of the study area), of which 365 km2 (7.2%) is optimal, 748 km2 (14.7%) is suitable, and 886 km2 (17.5%) is moderately suitable. Distance to the rivers, distance to the canals, and land use/land cover contributed most to predicting habitat suitability (10 and 49%, 40 and 16%, and 34 and 29%, respectively) during the wet and dry seasons. Habitat suitability increases as the mean diurnal range (bio 2) and temperature seasonality (bio 4) increase in both seasons and as the distance to rivers increases and decreases during the wet and dry seasons, respectively. Performance ratings were high, with AUC values (area under receiver operating curves) of 0.877 and 0.952 for the wet and dry seasons, respectively. Changing environmental variables and land use interact to influence habitat suitability and wildlife distribution. Our results are vital for understanding the influence of these variables on elephant distribution and movement and, thus, for adaptive management and migration corridor design to maintain species viability and ecosystem functionality in the study area.