Acute myeloid leukemia (AML) is an aggressive cancer of myeloid cells with high levels of heterogeneity and great variability in prognostic behaviors. Cytogenetic abnormalities and genetic mutations have been widely used in the prognostic stratification of AML to assign patients into different risk categories. Nevertheless, nearly half of AML patients assigned to intermediate risk need more precise prognostic schemes. Here, 336 differentially expressed genes (DEGs) between AML and control samples and 206 genes representing the intratumor heterogeneity of AML were identified. By applying a LASSO Cox regression model, we generated a 4-mRNA prognostic signature comprising KLF9, ENPP4, TUBA4A and CD247. Higher risk scores were significantly associated with shorter overall survival, complex karyotype, and adverse mutations. We then validated the prognostic value of this 4-mRNA signature in two independent cohorts. We also proved that incorporation of the 4-mRNA-based signature in the 2017 European LeukemiaNet (ELN) risk classification could enhance the predictive accuracy of survival in patients with AML. Univariate and multivariate analyses showed that this signature was independent of traditional prognostic factors such as age, WBC count, and unfavorable cytogenetics. Finally, the molecular mechanisms underlying disparate outcomes in high-risk and low-risk AML patients were explored. Therefore, our findings suggest that the 4-mRNA signature refines the risk stratification and prognostic prediction of AML patients.