The effect of extreme temperatures, precipitation and variations in other meteorological factors affect crop yields, and hence climate change jeopardizes the entire food supply chain and dependent economic activities. We utilize Deep Neural Networks and Gaussian Processes for understanding crop yields as functions of climatological variables, and use change detection techniques to identify climatological thresholds where yield drops significantly.