This study aimed to identify the corneal metabolic biomarkers for moderate and high myopia in human. We enrolled 221 eyes from 221 subjects with myopia to perform the femtosecond laser small incision lenticule extraction (SMILE) surgery. Among these, 71 eyes of 71 subjects were enrolled in the low myopic group, 75 eyes of 75 subjects in the moderate myopic group and 75 eyes of 75 subjects in the high myopic group. The untargeted metabolomics analysis was performed to analyze the corneal tissues extracted during the SMILE surgery using an ultra-high-performance liquid chromatography (UHPLC) coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometry (MS). The one-way analysis of variance (ANOVA) was used to identify the different metabolites among the three myopic groups, the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was used to reveal the different metabolites between moderate myopia and low myopia, and between high myopia and low myopia. The Venn gram was used to find the overlapped metabolites of the three datasets of the different metabolites. The stepwise multiple linear regression analysis was used to determine the metabolic molecules associated with manifest refractive spherical equivalents (MRSE). The Receiver Operating Characteristics (ROC) analysis was performed to reveal the corneal biomarkers for moderate and high myopia. The hub biomarker was further selected by the networks among different metabolites created by the Cytoscape software. A total of 1594 metabolites were identified in myopic corneas. 321 metabolites were different among the three myopic groups, 106 metabolites were different between high myopic corneas and low myopic corneas, 104 metabolites were different between moderate myopic corneas and low myopic corneas, and 30 metabolic molecules overlapped among the three datasets. The multivariate linear regression analysis revealed the myopic degree was significantly influenced by the corneal levels of azelaic acid, arginine-proline (Arg-Pro), 1-stearoyl-2-myristoyl-sn-glycero-3-phosphocholine, and hypoxanthine. The ROC curve analysis showed that azelaic acid, Arg-Pro and hypoxanthine were effective in discriminating low myopia from moderate to high myopia with the area under the curve (AUC) values as 0.982, 0.991 and 0.982 for azelaic acid, Arg-Pro and hypoxanthine respectively. The network analysis suggested that Arg-Pro had the maximum connections among these three biomarkers. Thus, this study identified azelaic acid, Arg-Pro and hypoxanthine as corneal biomarkers to discriminate low myopia from moderate to high myopia, with Arg-Pro serving as the hub biomarker for moderate and high myopia.