The distribution of Phlebotomus papatasi in Southwest Asia is thought to be highly dependent on temperature and relative humidity. A discriminant analysis model based on weather data and reported vector surveys was developed to predict the seasonal and geographic distribution of P. papatasi in this region. To simulate global warming, temperature values for 115 weather stations were increased by 1 degree C, 3 degrees C, and 5 degrees C, and the outcome variable coded as unknown in the model. Probability of occurrence values were then predicted for each location with a weather station. Stations with positive probability of occurrence values for May, June, July, and August were considered locations where two or more life cycles of P. papatasi could occur and which could support endemic transmission of leishmaniasis and sandfly fever. Among 115 weather stations, 71 (62%) would be considered endemic with current temperature conditions; 14 (12%) additional stations could become endemic with an increase of 1 degree C; 17 (15%) more with a 3 degrees C increase; and 12 (10%) more (all but one station) with a 5 degrees C increase. In addition to increased geographic distribution, seasonality of disease transmission could be extended throughout 12 months of the year in 7 (6%) locations with at least a 3 degrees C rise in temperature and in 29 (25%) locations with a 5 degrees C rise.