AbstractDynamic rate‐based approach for modeling and simulating batch distillation is presented. To predict separation efficiencies, mass transfer was considered explicitly using the Maxwell‐Stefan. Process dynamics were modeled by considering all relevant dynamic changes in the system, including the column periphery. The model, implemented at the large‐scale ABACUSS modeling environment, addresses implications of the dynamic and multicomponent nature of the process for its mathematical representation, the use of mass‐transfer coefficients, and the need for further experimental correlations. To validate the model, a series of separations of the highly nonideal quaternary system of methyl acetate, methanol, acetic acid, and water in a pilot‐plant batch‐distillation column with structured packings were conducted. The results show that a rate‐based approach can predict the column operation within the experimental error over the entire operation time without fitting of any kind. For the first time the use of a rate‐based approach on the ground of the Maxwell‐Stefan equations for a multicomponent batch‐distillation process was validated experimentally. Comparison of predictions of the rate‐based approach with simulations based on an equally tailored equilibrium‐stage model shows that the largest differences between the two approaches occur in short periods of very significant changes in the column profile. The additional effort of rate‐based modeling can be justified for the design of operating policies of multicomponent batch‐distillation processes.