Biodesulfurization is an advanced and efficient approach for eliminating resistant sulfur compounds from fossil fuels using specific microorganisms. This study focuses on the modeling and simulation of key aspects of the biodesulfurization process, including bacterial growth and death trends, substrate consumption rate, and product formation rate. To this end, exponential and logistic kinetic models were combined with ten specific bacterial growth rate models (Monod, Haldane, Aiba, Hinshelwood, Edward, Yano, Blackman, Andrews, Moser, and Webb( to characterize the biomass growth and death. The Luedeking-Piret model was utilized to describe substrate consumption and product formation rates. Accordingly, twenty modeling scenarios were developed, including combinations of growth/death kinetics, specific growth rates, substrate consumption, and product formation. These scenarios were evaluated and validated against experimental data from the literature on dibenzothiophene (DBT) degradation (as substrate) by a Mycobacterium strain, yielding 2-hydroxybiphenyl (2-HBP) as the final product. Statistical analysis shows that the exponential package predictions based on the Webb model, with SSEtotal = 0.087, RMSEtotal = 0.16, and R2mean = 0.976, provide the best fit and the lowest error when compared to the experimental data. This scenario can be applied to design and operate biodegradation units for resistant sulfur compounds from fossil fuels.