This study builds counties-specific panel data and establish a stochastic rice yield forecasting model by using a fixed effect panel model based on results calculating the coefficients for the meteorological factors, and by using a variety of weather scenarios. Rice yield prediction model developed estimating equations were set to rice yield as the dependent variable, and the average temperature, accumulated temperature, daily temperature range, sunshine hours as explanatory variables, by using panel data by counties in recent 10 years. Estimation results using a fixed-effects model was able to verify that an average temperature affects to yield as quadratic form, there appeared to be significantly affected by accumulated temperature in Heading period, an average temperature in Ripening period. a rice yield prediction model is meaningful in that we can see the forecasting results in the previous. not waiting the actual survey results provided by the National Statistical Office. because this forecasting estimates is sufficient rationale material by government supply & demand measures. Finally, the study leave to future challenges with respect to establishing a prediction model developed as combined with land productivity and environmental engineering factors.