Abstract: Protein glycosylation is one of the most abundant and structurally diverse post-translational modifications (PTMs) in eukaryotic systems. Unlike template-driven biosynthesis, glycosylation is synergistically regulated by multiple glycosyltransferases, glycosidases, and glycan transporters, resulting in extensive structural heterogeneity at both macroscopic and microscopic levels. This inherent complexity enables glycosylation to play an important role in protein folding, stability, quality control, intercellular communication, signal transduction, and immune regulation. The dysregulation of glycosylation is associated with a wide range of pathological conditions, including cancer, metabolic disorders, inflammatory diseases, and neurodegenerative diseases, highlighting the importance of comprehensive and site-specific glycoproteomic analysis. Recently, glycoproteomics based on liquid chromatography-mass spectrometry (LC-MS) has become a pivotal analytical platform for characterizing intact glycopeptides, which is capable of simultaneously identifying peptide backbones, glycosylation sites, and glycan structures. However, the low abundance of glycoproteins in complex biological samples, coupled with the low ionization efficiency and significant structural heterogeneity of glycopeptides, poses significant challenges for comprehensive and unbiased glycosylation analysis. Chemoenzymatic labeling strategies have emerged as powerful and versatile tools in MS-based glycoproteomics, offering unique advantages for the selective enrichment, identification, and quantitative analysis of protein glycosylation. By combining the strict substrate specificity of enzymes (e.g., glycosyltransferases and glycosidases) with the flexibility of chemical tagging reactions, these approaches enable precise characterization of glycosylation while maintaining compatibility with complex biological samples. Compared with conventional physicochemical or affinity-based enrichment methods, chemoenzymatic strategies provide improved structural specificity and enhanced adaptability to different glycosylation types. This review focused on recent methodological advances in chemoenzymatic labeling-assisted MS workflows for glycoproteomic analysis. Representative labeling strategies were systematically summarized according to glycosylation types, including N-glycosylation, O-GlcNAcylation, mucin-type O-GalNAcylation, and others. Among these chemoenzymatic labeling strategies, researchers have introduced innovations in probe design and synthesis, the selection of enzymatic tools, enrichment approaches, and tag-cleavage strategies, enabling these labeling methods to be more effectively integrated into glycoproteomic workflows. In addition to enrichment strategies, recent advances in tandem MS fragmentation modes and glycopeptide-centric data analysis software have significantly improved the scope and depth of glycosylation identification. The integration of chemoenzymatic labeling with advanced MS technology establishes a robust framework for high-throughput and quantitative glycoproteomics. In summary, the chemoenzymatic strategy connects chemical biology and MS, providing high selectivity, sensitivity in glycosylation analysis. Continuous innovation in enzyme engineering, labeled probe design, enrichment materials, and computational analysis is expected to further expand the scope of glycoproteomics, enabling a deeper understanding of the biological processes involved in glycosylation regulation and promoting translational applications in disease mechanism research and precision medicine.