OBJECTIVE To investigate the mechanism of Yifei xuanfei jiangzhuo formula （YFXF） against vascular dementia （VD）. METHODS The differentially expressed genes of YFXF （YDEGs） were obtained by network pharmacology. High-risk genes were screened from YDEGs by using the nomogram model. The optimal machine learning models in generalized linear， support vector machine， extreme gradient boosting and random forest models were screened based on high-risk genes. VD model rats were established by bilateral common carotid artery occlusion， and were randomly divided into model group and YFXF group （12.18 g/kg， by the total amount of crude drugs）， and sham operation group was established additionally， with 6 rats in each group. The effects of YFXF on behavior （using escape latency and times of crossing platform as indexes）， histopathologic changes of cerebral cortex， and the expression of proteins related to the secreted phosphoprotein 1 （SPP1）/phosphoinositide 3-kinase （PI3K）/protein kinase B （aka Akt） signaling pathway and the mRNA expression of SPP1 in cerebral cortex of VD rats were evaluated. RESULTS A total of 6 YDEGs were obtained， among which SPP1， CCL2， HMOX1 and HSPB1 may be high-risk genes of VD. The generalized linear model based on high-risk genes had the highest prediction accuracy （area under the curve of 0.954）. Compared with the model group， YFXF could significantly shorten the escape latency of VD rats， significantly increase the times of crossing platform （P＜0.05）； improve the pathological damage of cerebral cortex， such as neuronal shrinkage and neuronal necrosis； significantly reduce the expressions of SPP1 protein and mRNA （P＜0.05）， while significantly increase the phosphorylation levels of PI3K and Akt （P＜0.05）. CONCLUSIONS VD high-risk genes SPP1， CCL2， HMOX1 and HSPB1 may be the important targets of YFXF. YFXF may play an anti-VD role by down-regulating the protein and mRNA expressions of SPP1 and activating PI3K/Akt signaling pathway.