We develop a novel hybrid phenology matching model to robustly retrieve a diverse spectrum of crop phenological stages using satellite time series. The devised hybrid model leverages the complementary strengths of phenometric extraction methods and phenology matching models, and can achieve high accuracies for estimating corn and soybean phenological growth stages in Illinois. The paper can be found at https://doi.org/10.1016/j.isprsjprs.2021.09.011