This review summarizes advances in seasonal climate forecasting with a focus on agriculture, predominantly since the year 2000. The main research methods used were keyword searches in publisher-unaffiliated databases such as Web of Knowledge and in publication libraries of institutions known for their interdisciplinary work in climate forecasting and agriculture. Crop and livestock producers use seasonal climate forecasts for management decisions such as planting and harvest timing, field fertilization, or grazing. Agricultural users have often criticized lack of forecast skill and usability as well as a lack of understanding of user needs among forecast developers. Recently, interdisciplinary studies started exploring agricultural decision-making and integrating social science and climate science in order to improve the value of seasonal forecasts. Producer requests include direct and derived forecast products, such as total rainfall and consecutive dry days, information on uncertainty, and comparisons to previous years. The review explores single-model and ensemble forecasts, describes different measures of forecast value, and highlights economic and other agricultural decision factors besides weather and climate. It also examines seasonal climate forecasts from an agricultural perspective, explores communication challenges and how to overcome them, and delves into end-to-end forecast concepts that span forecast production to forecast application by end users.