The traditional “one-size-fits-all” methodology in disease diagnosis and patient management has been largely replaced by a more individualized strategy known as personalized medicine. In this evolving paradigm, biomarkers play a crucial role, serving as fundamental variables (features) in the advancement of machine learning and artificial intelligence-driven prognostic models. Among the diverse categories of biomarkers, metabolites are particularly significant due to their direct association with metabolic processes. Metabolomics, a discipline dedicated to the systematic examination of chemical signatures produced by cellular activities, offers valuable insights into metabolic functions. By analyzing metabolic profiles, researchers can gain a comprehensive understanding of cellular physiology, providing a direct functional assessment of an organism’s physiological state. The objective of this chapter is to develop a structured evaluation framework for nutritional biomarkers, explore predictive models for body mass index (BMI), and identify dietary patterns through the application of neural networks.