Based on continuous forest inventory data in respects of mean tree, sample tree and plot, growth models for mean height, mean DBH (diameter at breast height) and stand density were established by site classification method. The growth models were used for the updates of related factors in forest resources survey. Meanwhile, prediction models were built based on the relationships between stock, growth and consumption at stand level and related factors of age, mean height, mean DBH, stand density, etc. Anshan City in Liaoning Province was selected as demonstration research area. And model testing results showed that archival data of forest resources can be updated by growth model, and the annual growth and consumption of forest resources can be efficiently known by prediction models. This study could improve the annual monitoring ability of regional forest resource, and strengthen the pertinence and efficiency in the supervision and management of forest resources.