To investigate the long-term prognosis of patients with acute ischemic stroke (AIS) after intravenous thrombolysis with alteplase by establishing a multi-factor combined prediction model. Methods: A retrospective study was conducted to analyze 118 AIS patients treated with intravenous thrombolysis with alteplase. According to the modified Rankin scale (mRS) 90 days after thrombolysis, patients were divided into the good prognosis group (mRS score 0-2 points) and poor prognosis group (mRS score 3-6 points). Multivariate Logistic regression was used to analyze the factors affecting the 90-day prognosis of neurological function in AIS patients after thrombolysis with alteplase and to determine the joint predictive value Y. The ROC curve was used to verify the diagnostic validity of the Logistic regression model. Results: Among the 118 AIS patients, the prognosis was good in 56 patients (47.46%) and poor in 62 patients (52.54%). Compared to the good prognosis group, the poor prognosis group showed increased density of the middle cerebral artery sign and a higher baseline NIHSS score, a lower ASPECT score, and a greater bleeding rate following thrombolysis (all P<0.05). Multivariate Logistic regression analysis showed that ASPECTS score and baseline NIHSS score affected the long-term prognosis of intravenous thrombolysis (P<0.001), and the area under the ROC curve of the joint predictive value Y calculated by multi-factor Logistic regression was 0.740, with a sensitivity of 60.70% and a specificity of 74.19%. This was superior to using ASPECTS score (AUC=0.672, sensitivity =82.10%, specificity = 48.39% ) and baseline NIHSS score (AUC=0.693, sensitivity =75.00% , specificity =59.68% ) alone to predict prognosis after AIS thrombolysis. Conclusion: The hyperdense middle cerebral artery sign, ASPECTS score, and baseline NIHSS score of AIS patients before thrombolysis can all be used as 90-day prognostic factors. The joint variable Y calculated by multi-factor Logistic regression can better predict prognosis.