The current research was carried out to compare modeling methods for providing their predictive habitat models. For this purpose, study was conducted in Poshtkouh rangelands of Yazd province. For modeling, vegetation data in addition to site condition information including topography, climate, geology, soil and grazing intensity were prepared. Sampling was done in homogeneous units, which these units resulted from overlaying of hypsometry, aspect, slope, geology and vegetation maps. Within each unit 3-5 parallel transects with 300-500m length, each containing 30-50 quadrates (according to vegetation variations) were established.Sampling method was randomized-systematic. Quadrate size was determined for each vegetation type using the minimal area; hence suitable quadrate size for different species ranged from 1*2m to 10*10m (2-100 m2). Soli samples were taken from 0-30 and 30-80 cm in starting and ending points of each transect. Measured soil properties included gravel, texture, available moisture, saturation moisture, organic, matter, lime, gypsum, pH, electrical conductivity and soluble ions (Na+, K+, Mi+, Ca2+, cr, CO2-3, HCO-3) and So2-4). CCA and Logistic Regression (LR) techniques were implemented for plant species predictive modeling. To plants predictive mapping, it is necessary to prepare the maps of all affective factors of models. To mapping soil characteristics, geoestatistical method including variogram analysis and Kriging interpolation were used. Based on obtained predictive models for each species (through LR method) and for whole species (through CCA method) related predictive maps were prepared in GIS. The accuracy of predictive maps were tested with actual vegetation maps. Vegetation modeling results with CCA indicates that predictive map of vegetation corresponds with actual map (with high accuracy). Predictive maps of species, which have narrow amplitude, is as the same of actual vegetation map prepared for the study area. In general, LR will provide better specific-model, but CCA will provide a broader overview of multiple species.