A systematic methodology for the modeling and engineering analysis of industrial copolymerization reactors is presented. The methodology, especially suited for the scaling-up from laboratory experiments to pilot plant and industrial reactor level, consists of gradually building models of more complexity in a modular way as more information is obtained from experimental data and/or theoretical considerations. In the first stage, simple models for copolymer composition are written based on the Mayo-Lewis copolymerization equation and empirical copolymerization rate data for different reactor configurations (batch and CSTR) and reactor operations (steady state and some dynamic transients for the CSTR case). This set of models, which use minimal or no data fitting, is shown to be highly predictive. In a second stage, as kinetic information is obtained in the form of an expression for the copolymerization rate, either empirical or mechanistic, the models can be gradually expanded to include a full non-linear analysis of steady state multiplicities and other interesting phenomena, which can have an impact on the practical operation of the reactor. Also, as a complementary tool for the modeling of copolymerization reactors, a new model for the gel effect in polymerization, based on analogies with the familiar diffusion controlled reactions in heterogeneous catalytic reactors, is outlined and used. The methodology is illustrated with examples drawn from industrial reactors in bulk and emulsion, including some industrial reactor data.