Maternal metabolic dysregulation during pregnancy has been increasingly associated with altered immune outcomes in early life. However, the mechanisms of maternal metabolism and neonatal immune maturation have not been clearly defined. This study aimed to build a systems-level, simulation-driven framework for modeling neonatal immune maturation as a process of emergence from coupled signals of maternal metabolism, modulation of inflammation, and the regulatory dynamics of the immune system. The model was designed to simulate the time-dependent trajectories of neonatal immune maturation, incorporating metabolic indices for maternal fuel and form, cytokine gain parameters as a proxy for maternal inflammation, and coupled innate and adaptive immune parameters for maternal dysregulation across the four categories of pregnancy metabolism: normometabolic, overweight/insulin resistance, and gestational diabetes. The simulations suggest that under maternal dysmetabolic conditions, the immune maturation phenotype will be characterized by delayed and attenuated development of adaptive immunity but tempered or enhanced maturation of the innate immune system. Overall, the findings detail the predictive model that simulation-derived immune features of delayed maturation provide, coupled to a sensitivity analysis and outlining the dominant drivers of variability within the immune system: the balance of inflammation and the thresholds of adaptive activation. Most importantly, the study offers simulation-informed biomarkers of maternal metabolic conditions to assess the early immune risk of neonates, highlighting the translational capability of the findings.