Abstract: Multiple myeloma (MM) is a highly heterogeneous malignant plasma cell disease. Although the survival of patients has been significantly improved with the advent of new drugs in the past few years, molecular classification and prognostic evaluation are still challenging. Transcriptome studies based on gene expression profiling help decipher the complexity of MM, providing a new perspective for the molecular classification of MM. Gene expression profiling can assess the expression of coding and noncoding genes, mutations, and novel transcriptome modifiers, providing additional information about the treatment and prognosis of different MM subgroups. Gene expression profiling has been confirmed as an independent prognostic factor in multiple clinical trials to evaluate the prognosis of patients in different cohorts. Although gene expression profiling has not yet been clinically integrated into diagnosis and treatment, expression profiling data for myeloma have been studied at several research centers. Through cluster analysis of expression profiling data in public databases, clinical prognostic models are established to identify high-risk and low-risk patients in the dynamic evolution of the disease, predict treatment sensitivity, and find new therapeutic targets, making it possible to develop individualized treatment at the transcriptome level. This article reviews the application of gene expression profiling in the molecular classification of myeloma.