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Di(isononyl)cyclohexane-1,2-dicarboxylate (DINCH) is a plasticizer used in polyvinyl chloride (PVC) products, such as toys and food packaging. Because the use of DINCH is on the rise, the risk of human exposure to this chemical may likewise increase. Discovering markers for assessing human chemical exposure is difficult because the metabolism of chemicals within humans is complex. In this study, two mass spectrometry (MS)-based metabolite profiling data processing methods, the mass defect filter (MDF) method and the signal mining algorithm with isotope tracing (SMAIT) method, were used for DINCH metabolite discovery, and 110 and 18 potential DINCH metabolite signal candidates were discovered, respectively, from in vitro DINCH incubation samples. Of these, the 21 signals were validated as tentative exposure marker signals in a rat model. Interestingly, the two methods generated rather different sets of DINCH exposure markers. Five of the 21 tentative exposure marker signals were verified as the probable DINCH structure-related metabolite signals based on their MS/MS product ion profiles. These five signals were detected in at least one human urine sample. Of the five probable DINCH structure-related metabolite signals, two novel signals might be suitable exposure markers that should be further investigated for their application in human DINCH exposure assessments. These observations indicate that the MDF and SMAIT methods may be used to discover a relatively different set of potential DINCH exposure markers.