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The purpose of this study was to investigate the relationship between weather, technology, and corn and soybean yields in the U.S. Corn Belt. Corn and soybean yields, monthly temperature, and monthly precipitation observations were collected over 1960 through 2006 for Illinois, Indiana, and Iowa. Multiple regression models were developed based on specifications found in studies by Thompson (1962, 1963, 1969, 1970, 1985, 1986, 1988). Estimated models explained at least 94% and 89% of the variation in corn and soybean yields for each state, respectively. This research provided strong evidence that precipitation, temperature, and a linear time trend to represent technological improvement explained all but a small portion of the variation in corn and soybean yields in the U.S. Corn Belt. An especially important finding was that relatively benign weather for the development of corn since the mid-1990s should not be discounted as an explanation for seemingly high yields. The potential impact of this finding on the agricultural sector is noteworthy. Trend yield forecasts based on perceptions of a rapid increase in technology may eventually lead to poor forecasts. Unfavorable weather in the future may lead to unexpectedly low corn yields that leave producers, market participants, and policy-makers wondering how such low yields could have occurred despite technological improvements.