Objective To analyze the influencing factors of Acute Stress Disorder (ASD) in first-episode young and middle-aged stroke patients, and to construct a dynamic nomogram model, so as to facilitate early identification of ASD for medical staff. Methods A total of 298 first-episode young and middle-aged stroke patients in the first affiliated hospital, Jinzhou Medical University, were selected, then they were divided into a modeling group (n=208) and a validation group (n=90).Fifteen alternative factors were collected by using the bio-psycho-social medical model as a theoretical guide.LASSO regression and multinomial logistics regression were performed to screen risk factors of ASD.A dynamic nomogram model was constructed based on R-shiny, and the Bootstrap method was used for validation in the modeling group and the validation group. Results Totally 141 (47.32%) patients suffered from ASD.Five influencing factors of the Connor-Davidson Resilience Scale score, the Activities of Daily Living score, the National Institutes of Health Stroke Scale score, swallowing disorder, and hemiplegia were finally included through screening to construct the prediction model.The AUC in the modeling group was 0.884, and the AUC in the validation group was 0.879, and both of the validation calibration curves were close to the ideal curve. Conclusion This constructed dynamic nomogram model has good prediction perfor-mance, it provides a reference for ASD screening in first-episode young and middle-aged stroke patients.