A structural model is developed to simulate the probability distributions of corn prices by month. The intent is to determine the relationship between model specifications, based on a rational expectations competitive storage framework, and the probability distributions of monthly prices. Specifically, can a structural model generate corn prices with characteristics that are consistent with those observed in the 1990s? The model in this paper produces cash prices that inter alia have positively skewed distributions where the mean and variance increase over the storage season. The model also generates futures prices as conditional expectations of spot prices at contract maturity. The variances of these futures prices have realistic time-to-maturity and seasonal effects. The model is solved and simulated so that the consequences of making the model increasingly complex can be determined. A “curse of dimensionality” is inevitable with the increased complexity, resulting in lengthy computing times, but the final specification generates plausible probability distributions. In contrast to other models in the literature, our specification does not depend on the unrealistic assumption of zero stock-levels to generate skewed price distributions and the Abackwardation@ commonly observed in prices between crop years. Non-linearity in the supply of storage is achieved by modeling convenience yield. The model can be used to depict price behavior conditional on varying levels of the state variables, e.g., for large or small stock levels. Having created realistic probability distributions of prices, a logical next step is to use the distributions to appraise marketing strategies to manage price risk for corn.