Though it is of great importance, the majority of predictive models tend not to incorporate water chemistry in their formulations. The ionic diffusion model which was developed for CaCo3, is based purely on crystallization, and is one of the few models that incorporates water chemistry. This model does not provide satisfactory predictions for CaSO4 fouling. In this article, a new model is proposed for CaSO4 fouling which takes into account the effect of both crystallization and particulate fouling and is capable of predicting the fouling resistance during the cleaning cycle as well as the fouling cycle. A removal term is incorporated into the model, as the occurrence of particulate fouling for CaSO4 tends to weaken its crystalline structure and makes it more prone than CaCO3 to removal. Properties of the electrolyte were evaluated using MINTEQA2 computer code, which is approved by the U.S. Environmental Protection Agency. In this model, particulate fouling is estimated using the physical mechanism for particle transport and adherence, crystallization is estimated by ionic diffusion, and the removal term is approximated using hydrodynamics of flow and deposit properties. The inclusion of both crystallization and removal terms incorporates the effects of both water chemistry and hydrodynamics of the flow and provides a relationship which not only can predict fouling but also can predict dissolution, by change of water quality and/or stopping the operation, or removed by shear stress. Then proposed model was assessed using published experimental data. The results indicate that this model provides good predictions; the slope of predicted rates as a function of the experimental rates is 1.05. The experimental results, though limited in number suggest that crystallization is not the main or only mechanism contributing to CaSO4 fouling. Particulate fouling seems to be a major contributor. Further experimentation is in process to confirm the degree of particulate fouling and to substantiate or to modify the model accordingly.