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Examining the effects of climate change on the oak spatial distribution, as the main species of Zagros forests and its ecological and economic values is of significant importance. Here, we used species distribution models for simulating current climatic suitability of oak and its potential changes in 2050 and 2070. For this purpose, five regression-based and machine learning approaches, four climatic variables related to temperature and precipitation and two optimistic (RCP 2.6) and pessimistic (RCP 8.5)  greenhouse-gas scenarios were used. The results of measuring the accuracy of models by AUC indicated the good performance of all algorithms and Random Forest achieved the highest accuracy (AUC = 0.95) among other methods. The results showed that in both time periods and under both scenarios, changes will occur in oak spatial distribution and the most severe one would be a 42.9 percent loss in the oak climatic suitability in 2070 under pessimistic scenario (RCP 8.5).