Objective To investigate the risk factors of frailty in the elderly patients with dysphagia after acute cerebral infarction (ACI) and to establish a risk-prediction nomograph model. Methods A retrospective analysis was conducted of the clinical data of 195 elderly patients with dysphagia after ACI, who were treated in Suzhou Hospital of Integrated Traditional and Western Medicine from February 2020 to March 2022. They were randomly divided into a modeling group (n=130) and validation group (n=65) in a ratio of 2∶1, and those in the modeling group were further divided into frailty group (n=83) and non-frailty group (n=47) according to the occurrence of frailty. Data statistical analysis was conducted using SPSS 26.0. t test andχ² test was employed for inter-group comparisons based on the data type. Multivariate logistic regression was used to analyze the risk factors of frailty in the elderly patients with dysphagia after ACI in the modeling group, and a risk-prediction nomograph model was established using R3.6.1 software. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were drawn to evaluate the predictive efficiency, accuracy and clinical benefit of the nomogram model, and the validation group was used to evaluate the feasibility of the nomogram. Results The incidence of frailty in all 195 patients was 64.10% (125/195), 63.85% (83/130) in the modeling group, and 64.62% (42/65) in the validation group. Multivariate logistic regression analysis showed that the age above 75 years, course of swallowing disorders ≥21 d, living alone, self-financing, poor economic level, ≥3 complications, ≥3 medications, limb movement disorders, depression, malnutrition, and low social support level were risk factors for the frailty of elderly patients with dysphagia after ACI (OR=3.618,4.459,4.358,2.843,3.102,2.130,2.659,3.770,3.501,4.646,1.887; P＜0.05), and that dietary guidance was a protective factor (OR=0.570; P＜0.001). The ROC curve analysis showed that the area under the curve (AUC) of the prediction nomograph model was 0.853 for the modeling group and 0.844 for the validation group, with a sensitivity of 78.31% and 76.19%, and a specificity of 85.11% and 82.61%, respectively. The consistency index of the calibration curves was 0.798 for the modeling group and 0.793 for the validation group, and both calibration curves were close to the standard curve. The DCA results in both groups showed that the nomograph model had good net returns. Conclusion Age above 75 years, course of dysphagia, living alone, self-financing, poor economic level, ≥3 complications, ≥3 medications, limb movement disorder, depression, malnutrition, dietary guidance and low social support level are all influencing factors for the frailty in the elderly patients with dysphagia after ACI, and the nomograph model constructed based on the above factors is helpful to screen high-risk patients and guide early clinical intervention.