Systems modeling has long contributed to our understanding of metabolism and continues to be a powerful approach to solving metabolic engineering challenges. A primary challenge in metabolic engineering is the development of computational models that predict changes in cellular phenotype due to genetic perturbations. Here, we develop metabolic modeling tools for the analysis and engineering of microbial glycosylation systems. A variety of metabolic factors affect glycosylation, thus making it an ideal system for the application of metabolic model-guide strategies. In this study, we first review cellular network modeling, providing an overview of modern metabolic and signaling model construction approaches. Then, we develop a constraint-based metabolic model of glycosylation in E. coli using it to identify genetic perturbations that improve glycosylation efficiency in this host. Then, we develop a novel kinetic formulation for the dynamic modeling of cell-free metabolic networks, another potentially useful microbial-based glycoprotein production platform. We present a large-scale model of E. coli cell-free metabolism that will serve as a basis for model-guided cell-free metabolic engineering going forward. Finally, we develop a hybrid model of E. coli substrate utilization and regulation. Overall, this study provides powerful tools for the future metabolic engineering of microbial production hosts.