The study is aimed at choosing a better predictive model for the accurate description of SARS in Guangdong, Beijing and Mainland China in 2003. Observation and general experience have shown a sigmoid type of curve consisted of four phases comparable to the phases of the SARS growth in 2003 ： an initial lagging period, a period of accelerating change, a period of decelerating change, and a stationary period. In order to model the SARS system, a generalized Logistic growth function has been adopted in the paper. With the officially published data, the main features of evolution of the SARS population size have been obtained using the generalized Logistic growth model by optimizing technique. Then, for getting evolutionary process prediction, several classical S-models such as the Pearl, the Gompertz, Von Bertalanffy, and Richards are tested. The practice of calculations has found that the Gompertz model gives the most accurate results where fitting criteria are estimated as residual sum of squares (RSS).