This paper presents an expanded genome-scale metabolic model of *Escherichia coli* K-12 (jR904 GSM/GPR), which includes 904 genes and 931 unique biochemical reactions. The model is an extension of the previous model (jE660a GSM), which accounted for 660 genes and 627 reactions. The expanded model is elementally and charge balanced, and includes gene-to-protein-to-reaction (GPR) associations. Network gap analysis identified 55 open reading frames (ORFs) with putative functional assignments. The model's predictive capabilities are compared with those of jE660a, showing generally similar results but with differences under certain conditions. The importance of global proton balancing is highlighted, as it affects the flux of protons into and out of the medium, which is crucial for maximizing cellular growth. The model also enables the analysis of diverse datasets, such as transcriptomic and proteomic data, and can be used to design experiments to address specific biological questions. The expanded model, jR904, is a more complete and chemically accurate description of *E. coli* metabolism, providing a valuable tool for studying the genotype-phenotype relationship in *E. coli* K-12.This paper presents an expanded genome-scale metabolic model of *Escherichia coli* K-12 (jR904 GSM/GPR), which includes 904 genes and 931 unique biochemical reactions. The model is an extension of the previous model (jE660a GSM), which accounted for 660 genes and 627 reactions. The expanded model is elementally and charge balanced, and includes gene-to-protein-to-reaction (GPR) associations. Network gap analysis identified 55 open reading frames (ORFs) with putative functional assignments. The model's predictive capabilities are compared with those of jE660a, showing generally similar results but with differences under certain conditions. The importance of global proton balancing is highlighted, as it affects the flux of protons into and out of the medium, which is crucial for maximizing cellular growth. The model also enables the analysis of diverse datasets, such as transcriptomic and proteomic data, and can be used to design experiments to address specific biological questions. The expanded model, jR904, is a more complete and chemically accurate description of *E. coli* metabolism, providing a valuable tool for studying the genotype-phenotype relationship in *E. coli* K-12.