During　the　Covid-19　pandemic,　the　e-commerce　service　industry　has　played　a　significant　role　in　ensuring　the　development　of　e-commerce　and　promoting　the　innovation　of　new　business　models.　Grasping　the　trend　of　the　future　development　of　the　e-commerce　service　industry　leads　to　pushing　the　government　to　formulate　industrial　development　strategies　and　to　ensure　the　rapid　recovery　of　the　post-epidemic　economy.　This　paper　proposes　a　Multi-Model　Grey　Fusion　(MGF)　procedure　to　solve　the　reliability　and　robustness　problems　of　predicting　the　future　trend　of　the　e-commerce　service　induslly.　The　experimental　results　show　that　MGF　peforms　well　in　handling　the　small　data　prediction　problem　and　that　it　is　more　reliable　and　robust　than　the　four　single-base　models,　which　are　the　grey　model,　linear　regression,　back-propagation　neural　network,　and　support　vector　regression.　The　forecast　by　combining　the　MGF　with　the　rol/ingframework　shows　that　China＇s　e-commerce　service　industJy　will　keep　an　excellent　development　momentum.　Moreover,　the　market　size　is　expected　to　reach　RMB　8.　78　trillion　by　2025,　with　an　average　annual　growth　rate　of　8.8%.