Abstract: The present study aims to predict the action targets of antidepressant active ingredients of Xiaoyaosan to understand the "multi-components, multi-targets and multi-pathways" mechanism. Using network pharmacology, the reported antidepressant active ingredients in Xiaoyaosan(saikosaponin A, saikosaponin C, saikosaponin D, ferulic acid, Z-ligustilide, atractylenolide Ⅰ, atractylenolide Ⅱ, atractylenolide Ⅲ, paeoniflorin, albiflorin, liquiritin, glycyrrhizic acid and pachymic acid), were used to predict the targets of main active ingredients of Xiaoyaosan according to reversed pharmacophore matching method. The prediction was made via screening of the antidepressive drug targets approved by FDA in the DrugBank database and annotating the information of targets with the aid of MAS 3.0 biological molecular function software. The Cytoscape software was used to construct the Xiaoyaosan ingredients-targets-pathways network. The network analysis indicates that the active ingredients in Xiaoyaosan involve 25 targets in the energy metabolism-immune-signal transmutation relevant biological processes. The antidepressant effect of Xiaoyaosan reflects the features of traditional Chinese medicine in multi-components, multi-targets and multi-pathways. This research provides a scientific basis for elucidation of the antidepressant pharmacological mechanism of Xiaoyaosan.