Objective To investigate the influencing factors of post-stroke depression (PSD) 90 d after mechanical thrombectomy (MT) in acute ischemic stroke (AIS) patients with effective reperfusion. Methods The clinical data of AIS paitents with effective reperfusion in Neurovascular Center, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Jan. 2019 to Dec. 2020 were retrospectively analyzed. Effective reperfusion was defined as successful recanalization (modified thrombolysis in cerebral infarction grade≥2b) and good functional prognosis (modified Rankin scale score≤3) 90 d after MT. The baseline data of patients at admission were collected, including inflammatory indicators such as white blood cell (WBC) count and lymphocyte-to-monocyte ratio (LMR), and clinical data related to MT. The depression of patients was evaluated by patient health questionnaire-9 (PHQ-9). The patients were divided into PSD group (PHQ-9 score≥10) and non-PSD group (PHQ score＜10), and the differences of clinical characteristics between the 2 groups were analyzed. Multivariate binary logistic regression model was used to analyze the independent influencing factors of PSD, and receiver operating characteristic (ROC) curve was used to analyze the value of LMR alone and multivariate combination in predicting PSD. Results A total of 206 AIS patients with effective reperfusion were enrolled, including 68 patients (33.01%) in PSD group and 138 patients (66.99%) in non-PSD group. Multivariate binary logistic regression analysis showed that age (odds ratio ［OR］ ＝0.946, P＝0.011), Alberta Stroke Program early computed tomography score (ASPECTS) before thrombectomy (OR＝0.707, P＝0.008), WBC at admission (OR＝0.729, P＝0.006) and LMR at admission (OR＝0.596, P＝0.003) were independent influencing factors for PSD 90 d after MT in AIS patients with effective reperfusion. The ROC curve analysis showed that the area under curve (AUC) value of combination of the above 4 factors in predicting PSD was 0.795, and the AUC value of LMR alone in predicting PSD was 0.711. The optimal cut-off value of LMR was 2.96, with a sensitivity of 71.0% and a specificity of 64.7%. The incidence of PSD 90 d after MT in patients with LMR≤2.96 (86 cases) and LMR＞2.96 (120 cases) was 51.16% (44/86) and 20.00% (24/120), respectively, and the difference was statistically significant (χ²＝22.00, P＜0.001). Conclusion About 1/3 of AIS patients with effective reperfusion will develop PSD. Young age, large ischemic area at the beginning of onset, and low LMR and WBC count at admission are independent risk factors for PSD.