The relationship between plant species and environmental factors has always been a central issue in plant ecology. Defination of these numerical relationships is main core of potential habitat modelling of plant species. These models are applied to achieve information about spatial distribution of species, habitat suitability and evaluation of climate change effects on the species spatial distribution. Current study aimed to characterization of effective environmental factors on spatial distribution of Astragalus verus and produces potential habitat map using two statistical techniques logistic regression tree (LRT) and DOMAIN in a local scale. A stratified- random sampling was applied to pick up 100 sites (50 presence- 50 absence) of given species. Environmental maps were produced using geostatistics methods (Kriging and Inverse Distance Weight) by Arc GIS software for the whole study area. For each sampling site, presence or absence of given species as well as the environmental variables were recorded. Two statistical techniques, Logistic regression tree and DOMAIN were used to examine environmental variables related to the current species distribution. Maps of potential habitat of Astragalus verus were generated using these models. Both statistical techniques produced strong and useful models. LRT model indicated that species occurrence has high correlation with some environmental factors such as, mean daily temperature, clay, Electrical Conductivity and percentage of organic carbon of the soil. Also the results of PCA analysis to determination of the input factors to DOMAIN model show that 5 environmental factors (clay, Electrical Conductivity, percentage of organic carbon, precipitation of driest season, minimum temperature of coldest month) are the most important factors related to spatial distribution of this species. According to prediction map derived from the LRT and species response curves, Astragalus verus is highly probable in terms of climate condition in regions with mean daily temperature is more than 14.31 o C, and in terms of edaphic conditions in soils with Electrical Conductivity is less than 0.3 ds/m, clay 42 to 46 percent, organic carbon equivalent to 1 to 2 percent. Model evaluation was performed both by independent data set and model data. Cohen’s kappa value (kappa LRT =0.9, kappa DOMAIN =0.95) and area under receiver operating characteristics curve (AUC LRT =0.96, AUC DOMAIN =0.97) based on independent data set indicated the high power of models to create potential habitat map of Astragalus verus in local scales. Using optimal threshold from evaluation of models, habitat suitability map were generated for the species. Habitat suitability map derived from the DOMAIN and LRT demonstrate that 14118 hectare (14% of Study area) and 29000 (30% of study area) are suitable for species occurrence. According to kappa and AUC of ROC plot, Domain model has higher power prediction. The result of this study can be applied in management and rehabilitation programs. Keywords: Prediction Models, Potential habitat of Astragalus verus , Logistic Regression Tree Model, DOMAIN Model, Geographic Information Systems