The tear film overlying the epithelial cells of the eye's surface is vital to visual function, and its composition is reflective of ocular surface health. The ultrasmall volume of tears poses challenges in its analysis, contributing to the limited number of reports on the tear metabolome. In addition, using a standard clinical method of tear collection posed some confounding factors in metabonomic analysis. We sought to establish an analytical platform for the global characterization of human tear metabolites. Following information dependent acquisition (IDA) directed liquid chromatography-tandem mass spectrometry (LC-MS/MS), isotope pattern matched peak mining was performed using Extracted Ion Chromatogram (XIC) manager within the PeakView software. Sixty metabolites representing diverse compound classes were identified in human tears, most of which have not been previously reported. Selected metabolites were verified using pure standards. Unsupervised chemometric analysis showed good separation between tear samples and blanks (PC1 = 87%, R(2) = 0.91, Q(2) = 0.87). The results demonstrated the potential of our platform for untargeted metabonomic studies of eye diseases.