Robust modeling is a methodological approach focused on developing models that exhibit stable and reliable performance even in the presence of noisy data, outliers, or deviations from underlying assumptions. This field investigates techniques to minimize model sensitivity to such perturbations, thereby enhancing generalizability and trustworthiness in real-world applications.