This study revisits the large but inconclusive body of research on crop yield distributions. Using competing techniques across 3,852 crop and county combinations some inconsistencies in previous studies can be reconciled. We examine linear, polynomial, and ARIMA trend models. Normality tests are undertaken, with an implementable R-test and multivariate testing to account for spatial correlation. Empirical results show limited support for stochastic trends in yields. Results also show that normality rejection rates depend on the trend specification. Corn Belt corn and soybeans yields are negatively skewed while they tend to become more normal as one moves away from the Corn Belt.