〔Abstract〕 Objective To construct a nomogram prediction model for non-valvular persistent atrial fibrillation （PeAF）patients with left ventricular hypertrophy（LVH），followed by prognostic analysis through follow-up. . Methods This study retrospectively enrolled 949 patients with newly diagnosed and hospitalized non-valvular PeAF. Among them，403 patients presented with LVH. The cohort was randomly stratified into a training set（n= 665）and a validation set（n=284）. Univariate and multivariate Logistic regression analyses were employed to identify independent risk factors for PeAF complicated by LVH. A nomogram prediction model was subsequently constructed and evaluated for discriminative ability，calibration，and clinical utility using receiver operating character⁃ istic（ROC）curve analysis，calibration plots，and decision curve analysis（DCA）. Results Seven independent risk factors were ultimately identified and included in the prediction model：female sex，hypertension，diabetes， red blood cell distribution width-SD（RDW-SD）， body mass index（BMI）， left atrial diameter（LAD）， and left ventricular ejection fraction（LVEF）. The area under the ROC curve（AUC）in the training set was 0. 862（95% CI：0. 834-0. 890），and in the validation set，it was 0. 870（95% CI：0. 829-0. 911），demonstrating excellent pre⁃ dictive performance. Conclusion Independent risk factors for LVH in PeAF patients include female，hyperten⁃ sion，diabetes，RDW-SD，BMI，LAD，and LVEF. The prediction model built based on this can help early identi ⁃ fication of PeAF patients with high risk of LVH. At the same time，the incidence of major adverse cardiovascular events（MACE）is higher in PeAF patients with LVH. Patients with atrial fibrillation combined with LVH may ben ⁃ efit from catheter ablation.