In order to investigate the relationship between tree age and the correlated tree’s DBH (diameter at breast height) we simulated it with the method of artificial neural network, in which a BP (i.e. back propagation) was applied with the data from forest inventory measured in 1986-1988. The trees were two dominant tree species in northeastern China, Pinus koraiensis Sieb. et Zucc. and Abies nephrolepis (Trautv.) Maxim. The simulation was undertaken by taking the matrix of trees’ DBH as input vector and their correlated ages as output vector. The results showed that the accuracy from the model was as high as 0.9, indicating the method of BP neural network might be supplemental method to traditional one that making use of stand growth of trees