Econometrics forecasting exists accuracy problem, general rural grain production forecast method have Cobb-Douglas production function model, multiple linear regression model. With the difference of forecasting results between these two methods, therefore, in this paper introduces combination forecasting model to solve the above problem. Combination forecasting model adopted to improve prediction accuracy. The contributions of this paper build Cobb-Douglas production function model, multiple linear regression models, and combination forecasting model and offered procedures in its entirety solutions. This paper indicates combination forecasting model optimal solution and uses the calculated error metrics to measure the accuracy of these three prediction methods. By analyzing different indicators, we find that the combination forecasting model is superior to two other models in application. This paper can be used as an example about the forecast theory and practice problem.

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