During the past two decades, exploiting the metabolic processes (urease activity) of some microorganisms that lead to the precipitation of calcium carbonate (CaCO3) as a sustainable solution for producing self-healing cementitious materials in the construction industry has gained significant interest. Despite extensive efforts for experimental characterization of the effect of various influential factors such as the type of bacteria, urea and calcium concentration, temperature, and pH of the environment governing this phenomenon, the numerical modeling of this biochemical process has not advanced substantially due to its complexity and intertwined involved parameters. Among these influential parameters, pH is of considerable importance, as the initial pH level has an immediate effect on the urease activity of the bacteria, which subsequently affects the rate at which calcium carbonate precipitates. Additionally, during the CaCO3 precipitation process, pH fluctuates due to the production of by-products, such as ammonium, altering continuously the velocity of the bacteria’s urease activity. This chapter presents a numerical modeling for the CaCO3 precipitation by urease activity of Sporosarcina pasteurii via COMSOL Multiphysics®. The model considers the influence of calcium and urea concentrations and the initial pH level along with pH variations resulting from the production of by-products throughout the process. The model’s ability to predict CaCO3 content and the final pH level is assessed by comparing the computational results with experimental data from existing literature. Finally, a parametric analysis investigating the impact of the initial pH on the anticipated ultimate pH is presented.