Genome-scale kinetic models of metabolism are important for rational design of the metabolic engineering required for industrial biotechnology applications. They allow one to predict the alterations needed to optimize the flux or yield of the compounds of interest, while keeping the other functions of the host organism to a minimal, but essential, level. We define a pipeline for the generation of genome-scale kinetic models from reconstruction data. To build such a model, inputs of all concentrations, fluxes, rate laws, and kinetic parameters are required. However, we propose typical estimates for these numbers when experimental data are not available. While little data are required to produce the model, the pipeline ensures consistency with any known flux or concentration data, or any kinetic constants. We apply the method to create genome-scale models of Escherichia coli and Saccharomyces cerevisiae. We go on to show how these may be used to expand a detailed model of yeast glycolysis to the genome level. © Copyright 2013, Mary Ann Liebert, Inc.