To investigate the risk factors of poor prognosis 1 year after acute ischemic stroke (AIS) and to establish a nomogram risk prediction model. Methods: Clinical data of AIS patients who were consecutively admitted to 4 tertiary-grade A class hospitals from January to December 2015 were collected through the Xi’an Stroke Data Bank. The patients were followed up for 1 year after diagnosis. Univariate and multivariate Logistic analysis were applied to analyze the risk factors of poor 1-year prognosis. R software and the rms package were used to establish a nomogram risk prediction model for poor 1-year prognosis in AIS patients. Results: Multivariate Logistic regression analysis showed that age (OR=1.069, 95% CI 1.052～ 1.087, P=0.000), complication by pneumonia (OR=3.121, 95% CI 1.595～6.107, P=0.001), leukocyte count (OR=1.137, 95%CI 1.062～1.217, P=0.000), atrial fibrillation (OR=1.816, 95%CI 1.059～3.115, P=0.030), and NIHSS score at admission (OR=1.196, 95%CI 1.153～1.241, P=0.000) were independent risk factors for poor 1-year prognosis of AIS patients in the Xi’an area. Based on the above independent risk factors, a nomogram prediction model was established to predict poor 1-year prognosis in AIS patients. ROC curve analysis showed that the area under the curve (AUC) was 0.846, indicating good discrimination. The Hosmer-Lemeshow test showed no significant difference (χ2=12.22, df=8, P=0.142). Conclusion: A nomogram risk prediction model for poor 1-year prognosis in AIS patients was successfully established. This model has good differentiation and calibration.