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Olive crops have become a strategic sector in Andalusia, Spain, providing an element of social cohesion and territorial management, but identified as vulnerable under climate change. Their great socioeconomic importance makes the mitigation of climate change effects an important strategy. The main contribution of this paper is to show the application of Bayesian networks into climate change assessment using the evaluation of its impact over olive system in Andalusia. Both classification and regression models were learnt and validated to predict the potential olive grove distribution under an Intergovernmental Panel on Climate Change scenario. A lower error rate was obtained for the regression problem compared to classification. Results predict that climate change will lead to changes into the territorial distribution of olive crops, with a movement from the river valley to the uplands due to the impact of the predicted increase in temperatures.