not-yet-known not-yet-known not-yet-known unknown Background: The investigation of cuproptosis in relation to tumor development has been limited, particularly in Multiple myeloma (MM), indicating the need for further research. Our study aimed to examine the impact of cuproptosis-related genes on the prognosis of MM. Methods: Using the datasets, we filtered cuproptosis score-related differentially expressed genes (CRDEGs) by overlapping the DEGs between the MM and normal groups and between the high and low cuproptosis score groups. Additionally, key module genes were identified through weighted gene co-expression network analysis. A univariate Cox algorithm and multivariate Cox analysis were employed to obtain biomarkers of MM and build a prognostic model, before conducting independent prognostic analysis. Results: A total of 59 CRDEGs were filtered. Demonstrating their involvement in the COPII vesicle coat and endoplasmic reticulum protein processing and protein processing in the endoplasmic reticulum. Six prognosis-related biomarkers (PARP1, EDEM3, SEC23A, RSL24D1, TTC37, and SRP72) were obtained, and a prognostic model was developed. The performance of the model was verified using a test cohort (GSE136324 dataset) and a validation cohort (GSE24080 dataset). Risk score, age, albumin, International Staging System (ISS) score, and β2-microglobulin (B2M) was found to be a significant predictor of prognosis independently . Conclusion: As a result of this investigation, a set of six biomarkers associated with cuproptosis (PARP1, EDEM3, SEC23A, RSL24D1, TTC37 and SRP72) were screened to provide a basis for predicting the prognosis of MM.