In a rangeland ecosystem, vegetation and environmental factors are closely interrelated and interact with each other. Along with improvements in application of statistical methods and geographic information systems in plant ecology, many methods and approaches have been introduced to develop vegetation predictive maps around the world. This study aimed to evaluate the efficiency of maximum entropy (MAXENT), genetic algorithm (GARP) and DOMAIN models to predict the potential habitat of Bromus tomentellus Boiss and Festuca ovina L and evaluate the effects of climate change on their habitats in Isfahan province. Stratified random sampling method was used to collect occurrence data of the species and 60 sites were recorded from the habitats of these species using vegetation maps and field visits. The analytical models were developed using these data accordingly. Twenty occurrence sites were used as checkpoints to evaluate the models accuracy. Twenty two environmental layers including 3 physiographic variables and 19 climate variables were used in the modeling process.The relationships between species occurrence and selected environmental factors were explored using the models.The effects of climate change on geographic distribution of Br.tomentellus Boiss and Fe.ovina L were predicted using CCSM4 general circulation model under two scenarios of optimistic RCP2.6 and pessimistic RCP8.5. Elevation and precipitation of the hottest season (Bio18) were identified as the most influential factors affecting the distribution of the species based on the three models. Maximum entropy model was identified as the most appropriate model for both species. The performance of DOMAIN model to predict the species was poor based on the calculated. Response curves of the species revealedthat Br.tomentellus Boiss prefers habitats with elevation of 2500 to 3500 m asl,slopes of 10 to 30 degrees, annual precipitation of 240 to 260 mm and the average temperature of 8 to 10 ° C. Festuca ovina habitats occurs in elevation range of 2500-4000 m, slopes of 10 to 30 degrees, annual rainfall of 250 to 300 mm, and average temperature of 6 to 8° C. Although the modeling process indicated that 46.1 km 2 will be increased the size of appropriate habitats for Br. tomentellus in the study area based on the RCP2.6 climate change scenarios, there is 35.74 km 2 decline in size of these habitats based on the RCP8.5 scenario during the periods of 2050 and 2070. Results indicated that 76.07 and 106.9 km 2 will be added to the size of appropriate habitats for Fe. ovina under optimistic and pessimistic climate scenarios respectively because this species use C3 photosynthesis cycle and benefits from increasing the atmosphere Co 2 contents. Overlaying three models showed that 4269.6 km 2 and 1581.5 km 2 of the study area provide appropriate habitats for Br.tomentellus Boiss and Fe.ovina L . respectively. The size of co-occurrence areas of these two species were 658.98 km 2 , 2978.78 km 2 and 514.151 km 2 based on the MAXENT, GARP and DOMAIN models predictions respectively. Overall results revealed that these two perennial grasses have relatively common niche requirements. Keyword: CCSM4 , Domain,Genetic Algoritm, Maximum Entropy, Modelling