The gut microbiome plays a crucial role in human health and disease, with diet serving as a critical determinant of microbial composition and metabolic function. However, most existing nutrition databases are Western-centric, lacking comprehensive dietary information for non-Western populations, including Koreans. This limitation hinders the accuracy of in silico gut microbiome analyses and microbiome-disease associations. We developed the Korean Nutrition Model (KNM) to enhance in silico microbiome analyses by incorporating detailed macronutrient and micronutrient compositions reflective of Korean dietary patterns. KNM was constructed using a decision algorithm that integrates data from the Ministry of Food and Drug Safety and FooDB. Comparative analysis with the European Nutrition Model revealed significant differences in carbohydrate and vitamin compositions, which in turn influenced microbial growth rates and metabolic fluxes in in silico simulations. We further evaluated gut microbiota differences between Korean and European cohorts, including healthy individuals and inflammatory bowel disease patients. Our findings demonstrate that using an appropriate, population-specific nutrition model significantly improves microbiome analyses, reducing the risk of false associations. This study underscores the importance of regionally tailored dietary models and provides a framework for enhancing global dietary models to facilitate precision nutrition and microbiome-based disease interventions.