Abstract: 【Objective】Consider that periodic performance can improve the fitted effect of the model of forestry output value and predict the output value of forestry in the future, which can provide a reference for subsequent forestry departments to implement rational planning. 【Method】 Selecting data for the period 2004—2016, total output value of forestry, in view of the periodicity and trend of forestry output value and combining the traditional ARIMA model, we have designed a time series model of seasonal forestry output value. The model uses the CH test method to make up for the shortage of the traditional GM(1,1)model on the seasonal data test. 【Result】It is found that the seasonal time series model can not only predict the economic sequence based on annual data, but also can predict the economic sequence of the quarterly data and monthly data units or even daily data with higher prediction accuracy compared with the traditional GM(1,1)model.【Conclusion】It can be used by the forestry department to plan forestry output value because a seasonal time series model can effectively predict the periodicity and trend of forestry output value, and greatly improve the predictive accuracy.