The study of the gut microbiota has sparked a lot of interest in recent years because understanding its composition and function enables us to assess the health status of its host and helps prevent certain diseases. It is primarily composed of bacteria. The metabolic networks of the various identified bacteria in the microbiota have been reconstructed. The metabolic network is defined as the set of biochemical reactions that can take place within an organism, as well as the exchanges of metabolites between the organism and its environment. Across numerous organisms, efforts have been made to reconstruct this network, employing manual or automated processes. These comprehensive networks are stored in biological reference databases. One such database is the Virtual Metabolic Human, a repository housing all identified bacterial networks derived from studies on intestinal microbiota. These networks serve as a foundation for modeling organism behavior under specific dietary conditions. Our focus in this study involved employing Flux Balance Analysis on the 818 bacterial networks cataloged in the Virtual Human Metabolic database, exploring their responses across 11 distinct diets. The results of this statistical analysis revealed an intriguing trend: the bacteria primarily gravitated towards four specific diets, showcasing the highest values in biomass maximization. Notably, certain bacteria displayed considerable variability in their biomass maximization results across different diets. Moreover, the statistical analysis highlighted a strong correlation within certain bacterial families concerning the import/export dynamics of nutrients across varying dietary conditions. This sheds light on the nuanced relationship between bacterial responses and dietary compositions, offering valuable insights into their metabolic adaptability.