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This paper presents a computing approach to support harvest decisions in sugarcane utilizing artificial intelligence (AI). The proposed two-step Decision Support System (DSS) starts with an AI technique called Artificial Neural Network (ANN), which is utilized to forecast agronomical performance indicators. Next, an heuristic that uses Genetic Algorithms (GA) is applied to search, and then recommend, suitable areas to be harvested. This work includes some experiments with real data where the ideas put forward are tested. The results of these experiments proved our approach: (i) useful to decision makers and (ii) easily coupled to current Management Information Systems (MIS) existing in most sugarcane mills.