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In this paper, we evaluated the performance of the model AquaCrop for crop yield forecasting in the Brazilian semiarid (BSA) using meteorological observation and Eta model seasonal climate forecasts as input data. The study area is characterized by low rainfall that is poorly distributed throughout the rainy season; thus, the region’s agricultural productivity is vulnerable to climate conditions. AquaCrop was first calibrated using field experiments and subsequently applied to simulate an operational crop yield forecast system for maize under rainfed conditions. Simulations were performed with daily data for 37 growing seasons for the period 20012010. The seasonal climate forecast was used in combination with observed meteorological data to anticipate the crop forecast. Soil characteristics were derived from pedotransfer functions (PTFs). We were able to demonstrate the ability of the seasonal crop yield forecast system to provide timely and accurate information about maize yield at least 30 days in advance of the harvest. The development of improved crop yield forecasting system is crucial for implementing drought-preparedness measures in the BSA region.