ABSTRACT.- Crop type classification with satellite imageries is widely applied to support sustainable agricultural practices and for continuous crop monitoring [1], [2], [3]. In this work, we present a study for the classification of winter crops on a nationwide perspective for Uruguay. We have analyzed Uruguay's three most widely extended winter crops: wheat, barley, and rapeseed. We have trained a classifier based on XGBoost that uses temporal series built from Sentinel-2 image data. For training, we used the information from previous years and reported the results the following year. To our knowledge, this is the first work that proposes a clear and systematic way to classify winter crops in Uruguay based on historical data without needing samples of the actual year. We have obtained high precision and recall values for rapeseed and results comparable with other regions' work for wheat and barley. © 2024 IEEE.