Optimization of the thermomechanical control process of Nb microalloyed steels is a critical issue to industrial applications. The thermomechanical control process consists of multipass hot-rolling in the austenite region, above and below the non-recrystallization temperature TNR, and a controlling cooling process during the austenite to ferrite transformation. In the present study an integrated process chain model is employed comprising a physically based model and a phase field model. The physically based model is selected in order to determine the austenite static recrystallization and niobium carbonitrides Nb(C, N) strain-induced precipitation kinetics, as a function of the process variables. At each pass, the physically based model computes the softening fraction due to static recrystallization, the recrystallized grain size and the average grain size due to complete or partial recrystallization and grain growth, as well as the ferrite grain size after the austenite to ferrite transformation. In addition, the precipitated volume fraction of Nb(C, N), the remained amount of niobium in solution, the accumulated strain and the grain boundary area ratio due to partial or complete absence of recrystallization are obtained. Based on the calculated multipass recrystallization-precipitation-time-temperature diagrams, the phase field model is employed to describe the microstructural evolution during multipass hot-rolling in the austenite region and the accelerated cooling in the austenite and ferrite region. 2D phase field simulations are carried out using the commercial software MICRESS, while the required thermodynamic data for the austenite to ferrite transformation are provided in the form of locally linearized phase diagrams calculated by Thermo-Calc software. During multipass hot-rolling, the input data are a variable stored energy, a constant interfacial energy, a temperature dependent interface mobility including the solute drag effect, a nucleation site density and a critical Zener pinning pressure. During cooling in the austenite and ferrite region, the thermodynamic driving force for the austenite to ferrite transformation is included. Mapping the temporal evolution of the grain size and the high angle grain boundary distributions with respect to the process variables is the first step towards process chain design. After satisfying design criteria, like the microstructural degree of homogeneity, the optimum processing parameters can be derived.