Objective:To study the related factors of futile recanalization after endovascular treatment(EVT)for cerebral infarc-tion and construct a Nomogram column chart risk prediction model.Methods:144 patients with cerebral infarction treated with EVT in-tervention were selected as the research subjects,the patients were divided into effective recanalization group(n=78)and futile reca-nalization group(n=66),which accorded to whether ineffective recanalization occurred.The levels of clinical characteristic were com-pared between the two groups of patients.The patients were randomly divided into training set(n=101)and testing set(n=43)by 7∶3 ratio.In the training set,the Lasso regression method was used to screen feature factors,the impact factor was analysed by Logistic multiple regression model,the R language was used to draw risk prediction model,and conduct validation.The receiver operating char-acteristic(ROC)was used to evaluate the accuracy of the model.Results:There were 48 cases experienced futile recanalization in the training set,the incidence rate was47.52%,while there were18 cases experienced futile recanalization in the testing set,the incidence rate was 41.86%.The results of Logistic multiple regression analysis showed that comorbidities of infection(β=1.566,95%CI=1.217～18.839,P=0.025)and the NIHSS score at discharge(β=0.949,95%CI=1.841～3.626,P<0.001)were high-risk fac-tors for futile recanalization after EVT in cerebral infarction.A Nomogram risk prediction model for futile recanalization after cerebral in-farction EVT were established,which based on Logistic multivariate analysis results.The ROC analysis showed that the AUC of Nomo-gram column chart to determine futile recanalization were 0.845 and 0.862 respectively in the training set and testing set.Conclusion:The futile recanalization after EVT in cerebral infarction are related to comorbidities of infection and NIHSS score at discharge.Based on these,a Nomogram prediction model is established,it has high accuracy in predicting futile recanalization.