Nonlinear mixed effects model(NLMEM) is based on the relationship between the fixed and random effects in the regression function.The NLMEM has a competitive advantage in analyzing repeated measures data,the longitudinal data and multilevel data.This paper chose two kinds of two-level nonlinear mixed model to analyze basal area growth for Chinese Fir(Cunninghamia lanceolata). Model 1 is a general two-level NLMEM and Model 2 is based on Model 1 to further consider the fixed effects parameters changes with a specific factor. Firstly,through the analysis of these two models, this paper defined the basic model to build the two-level NLMEM.Secondly,665 kinds of models derived from Model 1 and 2 703 kinds of models derived from Model 2 were calculated and compared. The results showed that:for Model 1,there were 57 kinds of models converging,and when the formal parameter b_0 considered the block effects and plot effects,b_1 and b_4 only considered the block effects, the model fitted the best;and for Model 2,there were 24 kinds of model converging,and when the formal parameter bs considered the block effects and plot effects,b_1 only considered block effects and the fixed effects b_0 changed with any level of block level, Model 2 fitted the best.Finally,by comparing the traditional nonlinear regression model,Model 1 and Model 2,the results showed that Model 1 and Model 2 fitted better than the traditional nonlinear regression, and Model 2 was best fitting model. Nonlinear mixed effects model (NLMEM) is based on the relationship between the fixed and random effects in the regression function. NLMEM has a competitive advantage in analyzing repeated measures data, the longitudinal data and multilevel data. This paper chose two kinds of two- level nonlinear mixed model to analyze basal area growth for Chinese Fir (Cunninghamia lanceolata). Model 1 is a general two-level NLMEM and Model 2 is based on Model 1 to further consider the fixed effects parameters changes with a specific factor. the analysis of these two models, this paper defined the basic model to build the two-level NLMEM. Second, 665 kinds of models derived from Model 1 and 2 703 kinds of models derived from Model 2 were calculated and compared. The results said that : for Model 1, there were 57 kinds of models converging, and when the formal parameter b_0 considered the block effects and plot effects, b_1 and b_4 only considered the block effects, the model fitted the best; and for Model 2, there were 24 kinds of model converging, and when the formal parameter bs considered block effects and plot effects, b_1 only considered block effects and the fixed effects b_0 changed with any level of block level, Model 2 fitted the best .Finally, by comparing the traditional nonlinear regression model, Model 1 and Model 2, the results showed that Model 1 and Model 2 fitted better than the traditional nonlinear regression, and Model 2 was best fitting model.