Abstract: Phospholipids (PLs) play important roles in cellular regulation and cofactors. Profiling of phospholipids in biological samples could be helpful to understand in-depth knowledge of its physical function in biological organisms and the association with the development of diseases. Hence, it is necessary to develop robust and efficient method fit-for-purpose for clinical research and widely phospholipidomics application. The experiment was performed on an UPLC-Q-TOF MS system coupled with Acquity UPLC C18 BEH column (2.1 mm×100 mm×1.7 μm). Raw data were acquired in both positive and negative electron spray ionization (ESI) at MS^E mode, and processed using Progenesis QI software for phospholipids characterization. Composition of mobile phase, solvent for serum pretreatment and sonication time were investigated. Multivariate analyses, principal component analysis (PCA), including scores plots and loading plots were used for quick comparison and efficient identification of the investigated conditions. The optimized method was finally applied to four kinds of blood sample and a batch of clinical samples to verify the applicability. The optimal mobile phase composition was acetonitrile-isopropanol (50∶50, V/V) (coefficient of variation (CV) of retention time less than 0.1% and CV of peak area less than 10%). The result of heatmap visualization showed that pre-cold methanol-acetonitrile (1∶9, V/V) together with ultrasonic-assisted extraction for 2 min were the optimal method for the PLs extraction and non-phospholipids removal. Better reproducibility and extraction ability were also exhibited intuitively from the results of the score plots and loading plots after using PCA. The developed method was applied for four kinds of blood samples. For the purpose potentially applicable to metabolomics study, the method is also applied for plasma collected from clinical patients during diagnostic to determine the alternation of metabolic profiles. Seven major kinds of PLs consisting of 626 identifier in negative ESI and 302 identifier in positive ESI were identified including phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidic acid (PA), phosphatidylglycerol (PG), phosphatidylserine (PS), sphingo-myelin (SM). The results suggested that the developed method can not only satisfy phospholipidomics analysis of different kinds of blood samples, but also can be used in clinical research.