Multi-omics studies are becoming increasingly dependent on computational techniques to analyze the vast quantities of biological data available. Breakthroughs in next- generation DNA sequencing methods have allowed for the quick and inexpensive generation of large volumes of genomic information, and the online databases that collect and curate this data are growing rapidly. While the breadth of this information continues to expand, the depth of our understanding is limited by the availability of specialized research tools. Flux-Balance Analysis (FBA) is a mathematical approach for modeling metabolic networks and measuring the flow of metabolites through them. Using sequenced and annotated genomic data it is possible to reconstruct an organism’s complete metabolic map and predict phenotypic response to a set of imposed conditions. PyFBA is an open-source python package designed to generate, gap-fill, and simulate these metabolic models from functionally annotated genomes. Restructuring of the ModelSEED biochemistry database rendered the original release of PyFBA inoperable, but recent updates have repaired this incompatibility and expanded upon the features present in the original package.