The comparative analysis of metabolic networks can provide mechanistic understanding of species-specific differences of metabolism and associated biomarkers and drug targets for various applications. The laboratory rat has been used as a surrogate to study human biology for more than a century. We have generated the first genome-scale reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. Comparative analyses with these models captured metabolic features that distinguish rats from humans including vitamin C and bile acid synthesis pathways. After extensive manual curation and network reconciliation between iRno and iHsa, we generated biomarker predictions for rat and human hepatocytes by integrating gene expression changes in response to 76 pharmaceutical compounds and environmental toxicants. Biomarker predictions were validated with literature-based evidence for antipyretic and anti-gout medicines. Comparative analyses provided mechanistic insights into the selection of metabolite biomarkers common to rats and humans. These models will serve as powerful computational platforms for contextualizing experimental data and making functional predictions consistent with rat and human biology for clinical and basic science applications.=