The United States Department of Agriculture’s National Agricultural Statistics Service (NASS) conducts a prices received for grain survey each month. This survey is used to assess monthly prices received by farms for a given commodity at grain elevators. Prediction modeling was performed that compared NASS mid-month prices to Farm Service Agency (FSA) prices in order to determine which did the best job of forecasting the NASS whole-month price, potentially reducing respondent burden if the NASS mid-month price was not surveyed. This was performed on nine commodities, comparing three models on each. The prediction modeling and validation testing resulted in models for several commodities that accurately predict the mid-month price over time with low model variance and little or no bias. However, it was determined that the FSA prices did a relatively poor job at predicting the NASS whole-month price and should not be used.