Infant formula milk (IFM) is critical in many babies' diets and must be high-quality. Unfortunately, IFM has been an adulteration target by those attempting to make illegal profits and has suffered from contamination-related issues. This study’s main objective was to identify the most critical risks affecting IFM quality in the supply chain and determine mitigation strategies to improve IFM performance measurement. We developed a model to reduce adulteration and contamination rates in the infant formula milk supply chains (IFMSCs) and maximize safety. The steps to achieve the study’s objectives included (1) identifying the importance of IFMs for infant nutrition and their risks, (2) establishing mitigation criteria for evaluating IFMSC’s performance to maximize quality, and (3) analyzing each mitigation criterion to maximize IFM safety. Based on pairwise comparisons by professionals in the food supply chain (FSC) of decision-making, the hybrid Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) model were used to analyze and prioritize mitigation alternatives to develop a model that can prioritize and select the best criteria for maximizing IFM safety and achieving the study objective. According to the contamination quality risk agents, mitigation alternative (QR.M2) ranked highest in both tests. This study’s findings illustrate how vital it is to avoid risk when dealing with public health, especially infants’ health, and how IFM must undergo precise testing and quality checks at every supply chain stage to ensure quality.