Background: Acute myeloid leukemia(AML) is a highly heterogeneous hematological malignancy. Despite, increase in treatment options for AML over the past decade, prognosis for AML remain dismal. Numerous prognostic models have been developed for this disease, however nomograms predicting long-term survival in AML patients after induction chemotherapy(IA regimen) have not been described.Method: We constructed nomograms to predict disease-free survival(DFS) and overall survival(OS) by analyzing the cohort of patients with de novo non-M3 AML patients who underwent induction chemotherapy between June 2008 to August 2019. We utilized univariable and multivariable Cox proportional hazards regression analyses to obtain the selected variables for the nomograms. The discriminative ability and calibration were tested using C statistics, calibration plots, and Kaplan-Meier curves.Results: A total of 360 patients who underwent induction chemotherapy with IA regimen were included in the study. Of these 55% were male with a median age was 48 years. Using the univariate and multivariate analyses, the following variables were identified in the prediction of DFS: age(HR, 1.770; 95%CI, 1.160-2.702; P = 0.008), Hb(HR, 0.634; 95%CI, 0.462-0.870; P = 0.005), albumin(HR, 0.473; 95%CI, 0.363-0.615; P < 0.001) and cyto/molecular risk group(intermediate vs. favorable: HR, 1.614; 95%CI, 1.128-2.309; P = 0.001; poor vs. favorable: HR, 2.459; 95%CI, 1.645-3.676; P < 0.001) at the time of diagnosis, and allo-HSCT treatment(HR, 0.341; 95%CI, 0.234-0.497; P < 0.001). Factors which predicted OS were Hb (HR, 0.616; 95%CI, 0.438-0.866; P = 0.005), albumin (HR, 0.448; 95%CI, 0.340-0.591; P < 0.001), cyto/molecular risk group (intermediate vs. favorable: HR, 1.558; 95%CI, 1.068-2.275; P = 0.021; poor vs. favorable: HR, 2.348; 95%CI, 1.523-3.620; P < 0.001), allo-HSCT treatment (HR, 0.256; 95%CI, 0.166-0.396; P < 0.001), and age (HR, 1.528; 95%CI 0.980-2.382; P = 0.061). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.715 for DFS and 0.731 for OS). Conclusion: Independent predictors of survival and relapse risk after IA regimen for AML can be utilized to obtain survival nomograms. These nomograms were able to predict DFS and OS while having good calibration accuracy and discriminative ability on internal validation.