Abstract A method for classifying epidemiologic process models is presented along with a brief history of epidemiologic modeling. Epidemiologic models are distinguished as being associative or process models. Associative models attempt to establish etiology by observing the associations of various risk factors with the occurrence of disease. Process models attempt to quantitatively describe the course of disease in a dynamic population. This begins with a hypothesis regarding the underlying structural processes involved. A process model can be classified further according to: (1) how it models the effect of chance; (2) application perspective; (3) the mathematical treatment of time; (4) the computational treatment of individuals; (5) the method for determining a solution. The literature was reviewed for examples of applied epidemiologic process models. Examples are cited and classified according to the classification method proposed in this paper. Suggestions for appropiate applications of various models and further research are made.