Dyslipidemia is known as a common clinical disease that affects the health of millions of people around the world. The treatment of dyslipidemia with traditional Chinese medicine (TCM) is generally based on the accurate identification of disease syndromes. TCM syndromes are judged by traditional four-diagnosis method, which is subjective and fuzzy. Additionally, the judgment of TCM syndromes highly depend on doctors' own clinical experience. In this present study, we used nuclear magnetic resonance (NMR)-based serum metabolomics patterns to figure out the metabolic characteristics of different syndromes in patients with dyslipidemia. In total, we enrolled 60 patients with dyslipidemia (30 cases with Spleen and Kidney Yang Deficiency syndrome (SKYD) and 30 cases with Phlegm-Dampness Retention syndrome (PDR)) and 20 healthy controls. Based on NMR technique, the serum metabolomics patterns of patients with different syndromes and healthy controls were analyzed, in the hope of screening the different metabolites among different syndromes and the differential metabolic pathway, as well as exploring the changes of metabolic network among different syndromes of dyslipidemia. The results suggested that the serum metabolomics patterns based on NMR was used to identify serum metabolites in patients with dyslipidemia of SKYD and PDR as well as healthy controls. Besides, it was found that the metabolic patterns of these three groups can be distinguished well and the different metabolites between different syndromes can be screened. From the point of view of metabolites, the metabolic characteristics of the patients with PDR were mainly the accumulation of noxious metabolites, while the metabolic characteristics of the patients with SKYD were mainly the lack of metabolites with protective function. From the point of view of metabolic mode, there were different metabolic patterns in patients with different syndromes of dyslipidemia in liver metabolism, oxidation, inflammatory reaction as well as energy metabolism, which reflects the difference of syndromes from different angles. The differences in metabolic outcomes among patients with different syndromes of dyslipidemia had a close association with to the effects of multiple signaling pathways. This study identified the characteristics of serum metabolic model of patients with different syndromes of dyslipidemia and the potential differential metabolites and characteristic metabolic characteristics of syndromes in order to understand the biological characteristics of patients with dyslipidemia of SKYD and PDR.