Epilepsy is a cryptogenic neurological disorder characterized by recurrent seizures which may be precipitated by a variety of endogenous or exogenous factors, and usually occurs many months or years after a precipitating injury. Timely diagnosis and treatment at the early stage of epilepsy are very important for patients to prevent serious lesions and improve the quality of their life. In this study, the metabonomics approach based on the GC-MS technique, multivariate statistical analysis and the metabolism network analysis were applied to investigate metabolic changes in epileptic patients. The outcome of this study suggested that ten endogenous metabolites and five metabolism pathways were mainly involved and showed marked perturbations in epileptic patients. It not only enhances the understanding of the pathology of epilepsy, but also provides an experimental foundation for the therapeutic strategy of epilepsy. Furthermore, this work demonstrates the powerful predictive potential of the metabolic network analysis to neurological disease.