Subjective cognitive decline (SCD) is a preclinical stage before cognitive impairment, which has a high conversion risk into Alzheimer's disease. However, it is still unknown on the brain functional differences between SCD and healthy controls (HC) subjects. This study therefore proposed a complex brain network analysis based on graph theory. In this study, we selected functional magnetic resonance imaging (fMRI) scans from Xuanwu Hospital of Capital Medical University, including 27 SCD and 42 HC subjects. First, we constructed brain functional connectivity network to obtain brain network topology parameters, including clustering parameters, shortest path length, global efficiency, local efficiency, small world attributes, and modularity. Then, we compared differences on the parameters between two groups. As a result, both SCD and HC groups showed the characteristics of small world. Both global efficiency and local efficiency of HC groups were higher than those of the SCD group. In addition, we found that the global modularity of the SCD group (6 modules) was higher than the HC group (7 modules). Our findings indicated that there were differences in brain functional networks between SCD and HC groups. Graph theory analysis may be useful and helpful to discriminate SCD and HC subjects.