Abstract: Based on the measurement of 955 branch samples of 65 Korean pine (Pinus koraiensis) trees in 12 plots from Mengjiagang forest farm, Heilongjiang Province, and by using Poisson model and negative binomial model, the second-order branch count models for Korean pine were developed in this paper. AIC, Pseudo-R², RMSE and Vuong test were selected to compare the goodness-of-fit statistics of the models. The results indicated that the first-order branch count in a whorl was 3 to 5, with mean value of 4, and the first-order branch count in a whorl for Korean pine plantation associated with its own characteristics. The second-order branch count of the first-order standard branch had a large discrete degree. All subset regression techniques were used to develop the second-order branch count model. The negative binomial regression model E(Y)=exp(β₀+β₁lnRDINC+β₂RDINC²+β₃HT/DBH+β₄CL+β₅DBH) was selected as the optimal second-order branch count model (β represented the parameter, RDINC represented the relative depth into crown from tree apex, HT represented the total tree height, DBH represented the tree diameter at breast height, CL represented the crown length). Pseudo-R² of the optimal model was 0.79, the mean error was close to 0 and the mean absolute error was less than 7. For the developed model, the parameter values of lnRDINC, CL and DBH were negative, and the parameter values of RDINC² and HT/DBH were positive. With the increase of RDINC, the number of second-order branch had a peak value in the tree crown. On the whole, the precision of the second-order branch count model for Korean pine plantation was 96.4%, which would be suitable for predicting the second-order branch count for the study area and provide a theoretic basis for branch photosynthesis and biomass research.