Antibiotics play a vital role in veterinary and human medicine for combating infectious diseases and maintaining animal health. In dairy farming, antimicrobials are widely used for therapeutic and preventive purposes, including dry-cow therapy and medicated milk replacers for calves. While these practices are essential for livestock welfare and economic sustainability, they may result in antibiotic residues in milk and derived prod¬ ucts. Infants are particularly vulnerable to such residues due to rapid development, immature detoxification systems, and distinct exposure patterns. Consequently, the detection and control of antibiotic residues in infant milk formula (IMF) are of critical importance to public health. IMF is a fortified matrix rich in proteins and lipids, with added carbohydrates and minerals, which can induce stronger matrix effects and analyte–matrix in¬ teractions than regular milk. These characteristics require IMF-specific extraction and cleanup strategies, such as fat removal, protein precipitation, and chelation steps, to ensure accurate ultra-trace quantification. This review presents the first analysis of advanced analytical workflows developed over the past 10 years for the separation and quantification of antibiotic residues in IMF. Particular emphasis is placed on sample preparation approaches tailored to the complex IMF matrix and on chromatographic separation techniques, including high-performance liquid chromatography, ultra-high-performance liquid chromatography, and hydrophilic interaction liquid chromatography. In addition, this review highlights the growing role of chemometrics and artificial intelligence driven platforms in enhancing data interpretation and predicting contamination risks. By integrating analytical chemistry, food safety, and computational intelligence, this review provides a timely reference for researchers, regulators, and industry professionals worldwide.