Metabolic modeling has become an indispensable tool in modern microbiology, offering a systems-level perspective on bacterial physiology, pathogenesis, and therapeutic targeting. By integrating computational and mathematical frameworks with experimental data, researchers can simulate and predict metabolic behaviors under various conditions, including infection, drug treatment, and environmental stress. This chapter explores the diverse applications of metabolic modeling in the study of bacterial infections, highlighting how genome-scale models, machine learning, and systems biology approaches are transforming our understanding of microbial metabolism and its role in disease.