The Klebsiella pneumoniae Species Complex (KpSC) is a major cause of nosocomial infections globally, comprising seven closely-related Klebsiella taxa. Phenotypic assays have revealed metabolic diversity within the KpSC, but this has remained understudied as metabolism experiments are both time-consuming and cost intensive. Recently, genome-scale metabolic models have been used to investigate bacterial metabolism which, due to advancements in whole genome sequencing, can be generated at scale. These models compile genomic and biochemical data to reconstruct the metabolic network of an organism. We have previously developed a KpSC pangenome model based on 37 KpSC isolates. Here, we expand this model to include an additional 467 isolates, including representatives of many global problematic lineages. The updated pangenome model comprises 3,145 reactions, 2,433 genes and 1,348 growth phenotypes that can be simulated. Candidate metabolic reactions were identified using gene orthology to known metabolic genes, which were manually curated according to the literature. A subset of 37 isolates were used to determine median model accuracy for aerobic (94.6%) and anaerobic (79.1%) conditions when compared to BIOLOG PM1/PM2 growth plates for 129/190 carbon sources that could be predicted with the model. The construction of an updated KpSC pangenome reference model is a valuable resource for the scientific community as it can be used to build KpSC strain-specific models. These can then be used to investigate the relationship between KpSC metabolism and features such as drug resistance, identifying novel drug targets, virulence, ecology and epidemiology.