The application of pressurized capillary electrochromatography (pCEC) coupled with ultra violet (UV) detection has been investigated for the production of global metabolite profiles from human plasma, and its capabilities of classifying pancreatic cancer patients. The pCEC separation of plasma samples was performed on a RP column with gradient elution. The applied voltage, detection wavelength and type of acid modifiers on separation of plasma samples were optimized with pooled quality control (QC) sample. The stability and the repeatability of the methodology were also determined by the repeat analysis of QC sample. The effects of different scaling methods on the results of orthogonal partial least-squares discrimination analysis (OPLS-DA) based on pCEC-UV data set were also investigated. The results of the current study clearly showed the different phenotypes of metabolites of pancreatic cancer patients and healthy controls based on pCEC-UV plasma profiles. OPLS-DA data are shown to provide a valuable means of convenient classification. This work indicated that pCEC-UV method can be used as a cost-effective and information-rich, while relatively simple and inexpensive approach for plasma profiling on disease metabolomics studies.