Abstract: Taking 10 Pinus densata sampling trees at two plots located in Shangri-La city of Yunnan province as the research object，we measured and calculated single wood biomass growth and wood biomass growth rates based on stem analysis. Considering random effect of the plot effect and tree effect，the biomass growth and growth rate models were constructed by nonlinear mixed effect model technology，and all the different random parameter combinations were fitted and the variance and covariance structures of the models were analyzed. The results showed that， considering random effect of plot effect and tree effect model as the single-level mixed effect model and two-level mixed effect model，the fitting precision of the models was improved，especially two-level mixed effect model had the best fitting performance with the lowest values for AIC and BIC. Both biomass growth and growth rates two-level mixed effect models had the highest prediction accuracy，and the values reached 93.05% and 89.83%；the secondbest ones were the mixed effect model considering the random effect of tree effect，and the prediction accuracies were 88.34% and 88.74%，respectively；the prediction accuracies of models considering the plot effect were 83.99% and 67.27%，respectively；and the prediction accuracies of ordinary models were 87.00% and 87.11%，respectively.