There is a growing use of bioinformatics based methods in the field of Glycobiology. These have been used largely to curate glycan structures, organize array-based experimental data and display existing knowledge of glycosylation-related pathways in silico. Although the cataloging of vast amounts of data is beneficial, it is often a challenge to gain meaningful mechanistic insight from this exercise alone. The development of specific analysis tools to query the database is necessary. If these queries can integrate existing knowledge of glycobiology, new insights may be gained. Such queries that couple biochemical knowledge and mathematics have been developed in the field of Systems Biology. The current review summarizes the current state of the art in the application of computational modeling in the field of Glycobiology. It provides (i) an overview of experimental and online resources that can be used to construct glycosylation reaction networks, (ii) mathematical methods to formulate the problem including a description of ordinary differential equation and logic-based reaction networks, (iii) optimization techniques that can be applied to fit experimental data for the purpose of model reconstruction and for evaluating unknown model parameters, (iv) post-simulation analysis methods that yield experimentally testable hypotheses and (v) a summary of available software tools that can be used by non-specialists to perform many of the above functions.