Background: Although human milk (HM) confers important health benefits, how bioactive milk components (e.g., microbiota, oligosaccharides, and fatty acids) interact with infant genetics to influence childhood atopy remains poorly understood. Objective: We investigated interactions between infant genomic susceptibility and exposure to maternal human milk components (HMCs) and assessed whether integrating these genetic and milk features improves prediction of childhood atopy. Methods: Leveraging infant genomic and maternal HMC data from the CHILD Cohort Study, we conducted gene-milk interaction analysis using linear regression models that integrated polygenic risk scores (PRS) of nursing infants with multiple HMC types. Gradient-boosting machines (GBMs) were used to evaluate predictive performance of HMCs and infant PRS for childhood atopy. Results: Childhood atopy was associated with interactions between infant genomics (e.g., PRS associated with atopy) and exposure to specific human milk microbes (e.g., Abiotrophia, PBonf=0.005, β=0.29), as well as networks of co-occurring HMCs (e.g., a module containing Bifidobacterium longum, 2'-fucosyllactose, and eicosapentaenoic acid, P=0.009, β=-12.3). A GBM integrating HMCs and infant PRS achieved the highest predictive performance for childhood atopy with an area under the curve (AUC) of 0.78, outperforming models based on individual HMC types or PRS alone (AUC range: 0.54-0.63). Conclusion: Integration of maternal HMC exposures with infant genomics reveals interaction effects that contribute to prediction of childhood atopy. Understanding how early-life exposures such as HMCs impact the health of children differently depending on their genomic profiles may