The analysis of particulate polymerization processes is rather complicated due to the highly coupled chemical reaction, heat and mass transfer, and droplet/particle interaction phenomena. Furthermore, the physical properties (e.g., viscosity, density, mass- and heat-transfer coefficients, and interfacial surface properties) of the various phases typically vary by several orders of magnitude in the course of polymerization. The framework of population balances is ideally suited for the description of the complex dynamics of a wide range of particulate polymerization processes such as suspension, emulsion, dispersion, and gas-phase catalytic polymerizations. A number of predictive multidimensional and multicompartment population balance models, coupled with polymerization kinetics, have been developed in our laboratory for the calculation of the droplet/particle size distribution (PSD). The physical and chemical parameters affecting the evolution of the PSD are imbedded into the integrodifferential model equation(s) governing the process dynamics. In the present study, the general framework of population balance modeling is applied to typical particulate polymerization processes (e.g., suspension and gas-phase catalytic polymerizations) to predict the evolution of PSD in batch and continuous reactors in terms of the process operating conditions.