In-line multi-stage rotor–stator mixing systems are the recent industrial solution for mixing highly viscous liquids in a short period of time while minimizing temperature increase throughout the mixing process. Unlike their predecessors, namely batch mixers, in-line rotor–stator mixers facilitate a continuous mode of operation. However, there is a lack of detailed insight into their flow patterns, power consumption, and mixing behavior, as these mixers, particularly the multi-stage variants, are rarely studied in the scientific community. In this work, we propose a computational framework for modeling rotor–stator mixers using Lagrangian particle tracking and the immersed-boundary method. The tracer particles present an alternative to the commonly used Eulerian approach, which is susceptible to numerical diffusion. The use of the immersed-boundary method for modeling the motion of the rotor not only significantly reduces pre-processing time but also facilitates the modeling of various rotor–stator shapes with different motion patterns, making it possible to complete the modeling in a short time. The proposed method is used to investigate an industrial in-line multi-stage rotor–stator mixer, and the accuracy of the numerical results is verified by comparing them with experimental data. The simulations unveiled that at a rotational Reynolds number of up to 4000, significant back-mixing occurs, whereas for lower Reynolds numbers, the flow maintains a smooth forward motion without any back-mixing. The study also examines the residence time of the additive in the mixer, revealing that, particularly when dealing with high-viscosity mixtures, the additive has the potential to persist in the mixer for up to 3.5 times the theoretical residence time. Additionally, the obtained results are utilized to derive empirical equations that enable predicting the mixer’s performance for different Reynolds numbers.