Sustainable forest management requires accurate prediction from a growth and yield system. Such a system relies heavily on some measure of site productivity, which is often the site index. A model was developed for predicting dominant height growth and site index of even-aged cedar (Cedrus libani A. Rich.) stands in Turkey. Stem-analysis data from 148 trees were used for model development and validation. Six dynamic height-age equations were derived using the generalized algebraic difference approach (GADA). Autocorrelation was modeled by expanding the error term as an autoregressive process. Based on numerical and graphical analysis, a GADA formulation derived from the Chapman-Richards model was selected. Based on relative error in dominant height prediction, 80 years was selected as the best reference age. The resulting equation provided the best compromise between biological and statistical aspects and, therefore, is recommended for height growth prediction and site classification of cedar stands in Turkey.