Cutaneous leishmaniasis (CL) is now the main vector-borne disease in Iran. Two forms of the disease exist in the country, transmitted by Phlebotomus papatasi and Phlebotomus sergenti s.l. Modeling distribution of the vector species is beneficial for preparedness and planning to interrupt the transmission cycle. Data on sand fly distribution during 1990–2013 were used to predict the niche suitability. MaxEnt algorithm model was used for prediction using bioclimatic and environmental variables (precipitation, temperature, altitude, slope, and aspect). Regularized training, area under the curve, and unregularized training gains were 0.916, 0.915, and 1.503, respectively, for Ph. papatasi. These values were calculated as 0.987, 0.923, and 1.588 for Ph. sergenti s.l. The jackknife test showed that the environmental variable with the highest gain when used in isolation has the mean temperature of the wettest quarter for both species, while slope decreases the gain the most when it is omitted from the model. Classification of probability of presence for two studied species was performed on five classes using equal intervals in ArcGIS. More than 60% probability of presence was considered as areas with high potential of CL transmission. These areas include arid and semiarid climates, mainly located in central part of the country. Mean of altitude, annual precipitation, and temperature in these areas were calculated 990 and 1,235 m, 273 and 226 mm, and 17.5 and 16.4°C for Ph. papatasi and Ph. sergenti s.l., respectively. These findings can be used in the prediction of CL transmission potential, as well as for planning the disease control interventions.