Reactive granulation is a complex process which brings about a physical and chemical change in the raw materials. It is extensively used for the production of detergents through the dry neutralization reaction. In this paper, the dynamics of the reactive granulation process is captured using a coupled multidimensional population balance model (PBM) for the size enlargement and a diffusion-reaction (DR) equation for the kinetics of the reaction. This framework can capture the experimental observations that have also been reported in Schongut et al. (Ind. Eng. Chem. Res. 2011, 50, 11576). There are a few empirical parameters involved in the modeling framework for which a dynamic sensitivity analysis was employed to shortlist the parametric quantities that have the largest influence on the critical quality attributes. The model is calibrated against experimental results via the Nelder-Mead simplex algorithm for estimating the empirical parameters, and the model predictions were compared with experimental results. Both the parameter estimation and prediction results showed good agreement with the experimental results. The development in terms of a comprehensive mathematical model and the results as presented in this paper suggest the ability of this approach to make suitable model predictions which can significantly reduce the number of experimental trials required for process optimization and control.