Abstract: Metabolomics aims to systematically profile various small molecules (i.e., metabolites and lipids) in biological samples. Compared with genomics, transcriptomics and proteomics, metabolomics locates in the downstream of omics technologies, which links genotype with phenotype. Metabolomics is an important part of system biology. It has been widely applied to discover diagnostic biomarkers and understand disease pathogenesis. Due to the high structure diversity and numerous isomers of metabolites and lipids, high-accuracy and high-coverage analysis of complex biological samples remain the bottleneck for comprehensive metabolomics analysis. Recently, ion mobility-mass spectrometry (IM-MS) has emerged as a promising technology for metabolomics. Ion mobility is a separation technology for gas phase. The multiple collisions between ions and neutral buffer gas under the influence of an electric field in mobility cell were utilized to rapidly separate ions with different sizes, shapes and charges. Compared with traditional separation method (i.e., gas phase separation and liquid chromatography separation), this method can increase the peak capacity, reduce noisy signals, improve sensitivity and selectivity. More importantly, the collision cross section (CCS) value derived from IM-MS is a new physio-chemical property to aid the annotation of chemical structures of known and unknown metabolites. CCS value is high reproducibility among different labs and instruments, which is suitable to be standardized for database establishment and wide application on metabolomics analysis. Therefore, it is important to ensure the accurate CCS measurement and develop high coverage CCS database for metabolomics. There are three major types of commercially available ion mobility-mass spectrometers, including time-dispersive, spatial-dispersive, and confinement and selective release. Due to different instrument design, the CCS value calculation and calibration methods are different. It is necessary to use the appropriate calibration solutions and methods for CCS measurement. Recently, CCS databases for small molecules have been established, which can be classified as two types of experimental measurement and in silico curation. Metabolite standard was usually used to acquire the accurate experimental CCS values. However, the number of available metabolite standards limits the coverage of CCS database. Instead, with the progress of theoretical calculation and machine learning, CCS values significantly expand the coverage of CCS database in silico curation, which are also accurate enough for metabolites identification. In this review, the basic principles of commercial IM-MS instruments that commonly used for metabolomics were introduced. Then, the experimental measurement and calibration of CCS values for different IM-MS instruments were summarized. The available CCS databases used for metabolomics were demonstrated. Finally, the applications of CCS values to support metabolomics were discussed.