Recently, many new diagnostic biomarkers have been developed for colorectal cancer. We chose 2 methods with high diagnostic efficiency, the detection of serum microRNA and metabolomics based on gas chromatography/mass spectrometry (GC/MS), and aimed to establish appropriate models. We reviewed the diagnostic value of all microRNA identified by previous diagnostic tests. We selected appropriate microRNA to validate their diagnostic efficiency, and determined the optimal combination. We included 85 patients with colorectal cancer (CRC) and 78 healthy controls (HC) and detected the expression of the microRNA. GC/MS analysis was conducted, and we used 3 multivariate statistical methods to establish diagnostic models. The concentrations of carcinoembryonic antigen (CEA) and carbohydrate antigen 19‐9 (CA19‐9) were detected for comparison with the novel models. Ultimately, 62 published studies and 63 microRNA were included in this review. MiR‐21, miR‐29a, miR‐92a, miR‐125b and miR‐223 were selected to further validate their diagnostic value. The serum levels of the 5 microRNA in CRC patients were significantly higher than those in the HC. The combination of miR‐21, miR‐29a, miR‐92a and miR‐125b had the highest area under the curve (AUC) at 0.952, with a sensitivity of 84.7% and a specificity of 98.7%. The GC/MS analysis exhibited an excellent diagnostic value and the AUC reached 1.0. With regard to traditional biomarkers, the AUC of CEA and CA19‐9 were 0.808 and 0.705, respectively. The application prospects are good for microRNA and metabolomics as new diagnostic methods because of their high diagnostic value compared with traditional biomarkers. The combination of miR‐21, miR‐29a, miR‐92a and miR‐125b had the highest area under the curve (AUC) at 0.952 with a sensitivity of 84.7% and a specificity of 98.7%. The GC/MS analysis exhibited an excellent diagnostic value and the AUC reached 1.0. There is a good application prospect for microRNAs and metabolomics as new diagnostic methods because of their high diagnostic value compared with traditional biomarkers.