To create a personal prognostic model and modify the risk stratification of paediatric acute myeloid leukaemia, we downloaded the clinical data of 597 patients from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database as a training set and included 189 patients from our centre as a validation set. In the training set, age at diagnosis, -7/del(7q) or -5/del(5q), core binding factor fusion genes, FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD)/nucleophosmin 1 (NPM1) status, Wilms tumour 1 (WT1) mutation, biallelic CCAAT enhancer binding protein alpha (CEBPA) mutation were strongly correlated with overall survival and included to construct the model. The prognostic model demonstrated excellent discriminative ability with the Harrell's concordance index of 0.68, 3- and 5-year area under the receiver operating characteristic curve of 0.71 and 0.72 respectively. The model was validated in the validation set and outperformed existing prognostic systems. Additionally, patients were stratified into three risk groups (low, intermediate and high risk) with significantly distinct prognosis, and the model successfully identified candidates for haematopoietic stem cell transplantation. The newly developed prognostic model showed robust ability and utility in survival prediction and risk stratification, which could be helpful in modifying treatment selection in clinical routine.