AERMOD and CALPUFF air dispersion models were evaluated for their performance in predicting nitrogen dioxide (NO2) and sulfur dioxide (SO2) in Maptaphut industrial area in Thailand. Emission data were obtained from 292 point sources in the study domain. Modeled results were compared with those measured data from 10 receptor sites. Evaluation of model performance was carried out by using statistical analysis. Overall results revealed that AERMOD provided more accurate results than CALPUFF model for both NO2 and SO2 predictions. As for the highest value, results from robust highest concentration analysis indicated that AERMOD had better performance in predicting extreme high-end concentration than CALPUFF.