Numerous people die of paraquat (PQ) poisoning every year in the world. Although several studies regarding paraquat (PQ) poisoning have been conducted, the metabolic changes in plasma remain unknown. In this study, the metabolomics of 15 PQ poisoned patients with plasma PQ concentrations in excess of 0.1 µg/mL and 16 healthy volunteers were investigated. The plasma samples were evaluated through the use of gas chromatography-mass spectrometry (GC/MS) and analyzed by partial least-squares discriminant analysis (PLS-DA). Based on the metabolomics data, a support vector machine (SVM) discrimination model was developed. The results showed the plasma levels of urea, glucose oxime and L-phenylalanine decreased and cholesterol increased in PQ poisoned patients in comparison to healthy volunteers. The SVM discrimination model was developed, and performed with a high degree of accuracy, to distinguish PQ poisoned patients from healthy volunteers. In conclusion, metabolic pathways including the urea cycle, and amino acid, glucose, and cholesterol metabolism were impaired after PQ poisoning. An SVM discrimination model, based on metabolomics data, was established and may become a new powerful tool for the diagnosis of PQ poisoning.