The Mycobacterium tuberculosis complex includes bovine and human strains of the tuberculosis bacillus, including Mycobacterium tuberculosis, Mycobacterium bovis and the Mycobacterium bovis BCG vaccine strain. M. bovis has evolved from a M. tuberculosis-like ancestor and is the ancestor of the BCG vaccine. The pathogens demonstrate distinct differences in virulence, host range and metabolism, but the role of metabolic differences in pathogenicity is poorly understood. Systems biology approaches have been used to investigate the metabolism of M. tuberculosis, but not to probe differences between tuberculosis strains. In this study genome scale metabolic networks of M. bovis and M. bovis BCG were constructed and interrogated, along with a M. tuberculosis network, to predict substrate utilisation, gene essentiality and growth rates. The models correctly predicted 87-88% of high-throughput phenotype data, 75-76% of gene essentiality data and in silico-predicted growth rates matched measured rates. However, analysis of the metabolic networks identified discrepancies between in silico predictions and in vitro data, highlighting areas of incomplete metabolic knowledge. Additional experimental studies carried out to probe these inconsistencies revealed novel insights into the metabolism of these strains. For instance, that the reduction in metabolic capability observed in bovine tuberculosis strains, as compared to M. tuberculosis, is not reflected by current genetic or enzymatic knowledge. Hence, the in silico networks not only successfully simulate many aspects of the growth and physiology of these mycobacteria, but also provide an invaluable tool for future metabolic studies.