We investigate the ability of three different crop models of varying complexity for capturing El Niño-Southern Oscillation (ENSO) based climate variability impacts on the U.S. Corn Belt (1981-2010). Results indicate that crop models, irrespective of their complexity, are able to capture the impacts of climate variability on yield. Multiple-model ensemble analysis provides best results. There was no significant difference between using on-site and gridded meteorological datasets to drive the models. These results highlight the ability of using simpler crop models and gridded regional datasets for crop-climate assessments.