Our study conducted a questionnaire survey on stroke patients during rehabilitation in Jianhu County people’s Hospital. Demographic data and health-related indicators were collected. Logistic regression analysis was employed to identify the influencing factors, and the nomogram model was constructed to predict the quality of life. The results showed that family monthly income ≥3000 yuan, having systematic rehabilitation training, higher social support score, having one’s own hobby, family care, visited times ≥2, treatment time ≥3h after the onset of stroke have increased 3.65-9.95 times of high quality of life in the rehabilitation period of middle-aged and elderly stroke (P<0.001). Compared with total disability, severe, moderate and mild disability increased quality of life by 2.86 times, 3.40 times, and 223.85 times, respectively (P<0.05). While the proportion of patients with other concomitant diseases, psychological symptoms of anxiety or depression, and treatment time ≥3h after onset decreased the quality of life (P<0.001). The nomogram model constructed in our study predicted the total score up to 280 points. When the predicted scores of these factors reached 164 or above, the incidence of patients with high quality of life reached 90% or above, and the verification results of the nomogram model suggesting that the accuracy and precision were good. Therefore, it is recommended that the medical sector identify and intervene early on controllable influencing factors supplemented by predictive models, and develop personalized rehabilitation programs to improve the quality of life of patients.