In this study in order to regionalize the areas in south and south west of Iran for agricultural studies, 44 synoptic stations located in Khuzestan, Charmahal Bakhtiari, Ilam, Kogeluyeh and Booyer Ahmad, Hormozgan, Fars and Bushehr, were selected. Obtained data of 15 climate parameters effecting on agricultural crops were collected for a 20 year period. In order to determine the most effective climate-agricultural parameters, the method of Principal Component Analysis (PCA) was utilized. The first three components causing 85% of variances of variables were selected and among these three components, 11 variables were identified as the most effective climate-agricultural parameters. These parameters include: Average of minimum temperature, Average of mean daily temperature, Number of days with maximum temperature equal 30 and above, Number of days with precipitation, Number of days with thunder storm, Number of cloudy days, Average of relative humidity, Monthly total of precipitation, Number of days with snow or sleet, Number of clear days, Number of partially cloudy days. Data obtained from selected climate variables, were analyzed by cluster analysis (Average linkage). After obtaining the dendrogram, it was cut in the place that 9 climate regions were produced for 44 selected synoptic stations. Moreover, in order to evaluate of obtained results of cluster analysis, discriminant analysis was utilized. The results indicated that 97.7% of synoptic stations were placed in their right groups correctly. Relative similarity in vegetation and crop types in each climate class indicated that the derived climate classification could be used for agricultural studies as a general guidance.