【Objective】 The estimation of large-scale forest carbon storage has attracted much attention, and the establishment of forest tree layer carbon storage model is an effective method to evaluate forest carbon storage. 【Method】 A total of 207 plots in a Korean pine plantation in Heilongjiang Province (Dongjingcheng, Linkou, Maoershan, Mengjiagang) were studied for modeling stand carbon storage, and choose the aggregation method, adjustment method, disaggregation method as the additivity method of establishing the stand carbon storage model, the research used the weighted regression to eliminate the heteroscedasticity of the carbon storage model, and adopted the leave-one-out cross validation method to evaluate the carbon stock model based on three additivity methods. 【Result】 There were slight differences between the fitting results of the forest carbon storage model based on the three additivity methods. The overall prediction ability of the aggregation method was slightly better than the adjustment method and the disaggregation method, and the specific prediction precision was ranked as the aggregation method > adjustment method > disaggregation method. When predicting stand total carbon storage, the predictability of the three additivity methods in different stand basal area intervals was not consistent. 【Conclusion】 The stand carbon storage model based on aggregation method was more suitable for the prediction of carbon storage of Korean pine plantation in Heilongjiang Province. However, when predicting the total carbon storage of Korean pine plantations, the appropriate additive method should be selected according to the stand basal area interval.