Abstract: 【Objective】Site indexes are commonly used for forest site quality evaluation. This study used a generalized algebraic differential approach(GADA)to develop dynamic site index models for Chinese fir plantations in the Jiangle National Forest Farm in Fujian Province.【Method】Using data of 24 permanent sample plots and by conducting stem analysis of 20 dominant individual trees, dynamic site index models were developed separately from Bertalanffy-Richards, Lundqvist-Kolf, and Hossfeld functions. Among the derived models, the best one was determined by comparing the statistical and biological features.【Result】Six dynamic site index models showed a robust fit with an adjusted coefficient of determination(R²_adj)of about 0.9. The Hossfeld model was identified as the best model, in which a=b1+X and b=b2/X were parameters related to the site condition. This model is recommended for dominant tree height prediction and forest site quality evaluation in the studied region.【Conclusion】The method applied in this study is accurate and effective for site index model derivation. It is necessary to consider graphical analysis in addition to statistical indicators when choosing the best growth model in order to satisfy both statistical and biological characteristics.