The population of snow leopard (Panthera uncia) is declining across their range, due to poaching, habitat fragmentation, retaliatory killing, and a decrease of wild prey species. Obtaining information on rare and cryptic predators living in remote and rugged terrain is important for making conservation and management strategies. We used the Maximum Entropy (MaxEnt) ecological niche modeling framework to predict the potential habitat of snow leopards across the western Himalayan region, India. The model was developed using 34 spatial species occurrence points in the western Himalaya, and 26 parameters including, prey species distribution, temperature, precipitation, land use and land cover (LULC), slope, aspect, terrain ruggedness and altitude. Thirteen variables contributed 98.6% towards predicting the distribution of snow leopards. The area under the curve (AUC) score was high (0.994) for the training data from our model, which indicates predictive ability of the model. The model predicted that there was 42 432 km² of potential habitat for snow leopards in the western Himalaya region. Protected status was available for 11 247 km² (26.5%), but the other 31 185 km² (73.5%) of potential habitat did not have any protected status. Thus, our approach is useful for predicting the distribution and suitable habitats and can focus field surveys in selected areas to save resources, increase survey success, and improve conservation efforts for snow leopards.