Objective To construct a dynamic nomogram prediction model, to analyze the influencing factors of frailty in elderly patients with hypertension in the community, and to provide a reference for developing targeted intervention. Methods Information on patients with hypertension was extracted from the China Health and Retirement Longitudinal Survey and randomly divided into a training set （n=1 160） and a validation set （n=494） in a ratio of 7∶3.The best predictors were screened by using LASSO me-thod, and the logistic regression model was used to analyze the influencing factors of frailty in hypertensive patients and develop a nomogram prediction model. Area under the ROC curve （AUC）, Hosmer-Lemeshow test, calibration curve and decision curve analysis （DCA） were used to evaluate the predictive performance of the nomogram prediction model. Results A total of 1 654 elderly hypertensive patients were screened, of whom 560 （33.86%） were complicated by frailty. Such 10 variables as education level, grip strength, BMI, depression, cognitive impairment, self-rated health, metabolic diseases, cardiovascular/cerebrovascular diseases, respiratory diseases, and gastrointestinal diseases were included in the prediction model. The AUC of the ROC curve of the prediction model were 0.883 （95%CI:0.863-0.903）in the training set and 0.887 （95%CI:0.857-0.916） in the validation set respectively.The P value of the Hosmer-Lemeshow test was 0.825 in the training set and 0.410 in the validation set respectively. The calibration curves showed a favorable consistency between predicted and actual values. DCA showed that the model had good net benefits and predictive accuracy. Conclusion This dynamic nomogram has good predictive performance, which can serve as a convenient and effective tool for community medical staff to assess the risk of frailty in patients with hypertension.