The　excavation　adaptability　evaluation　decision　process　for　the　TBM　(tunnel　boring　machine)　in　long　and　large　tunnels　under　complex　geological　conditions　is　an　uncertain　and　fuzzy　problem　affected　by　multiple　factors.　Aiming　to　shift　the　status　quo　of　TBMs　tunneling　adaptability　evaluation　and　the　ineffective　use　of　related　accident　cases,　the　TBM　tunneling　adaptability　evaluation　method　based　on　case-based　reasoning　is　proposed　and　researched.　The　case-based　reasoning　method　can　use　existing　engineering　experience　and　knowledge　to　answer　newly　encountered　problems,　and　can　accurately　and　efficiently　evaluate　the　adaptability　of　TBM　tunneling.　Based　on　the　nearest　neighbor　method,　this　paper　establishes　the　calculation　formula　of　TBM　tunneling　adaptability　similarity.　Based　on　the　statistical　analysis　method,　the　evaluation　indicators　that　play　a　relatively　important　role　in　the　system　are　selected,　and　the　TBM　tunneling　adaptability　evaluation　index　system　is　constructed.　The　analytic　hierarchy　process　(AHP)　is　used　to　determine　the　weight　of　the　evaluation　indicators　at　each　level.　According　to　the　characteristics　of　TBM　tunneling　adaptability　evaluation,　the　overall　design　of　the　case-based　reasoning-based　TBM　tunneling　adaptability　evaluation　decision　system　CBR-TBMEAEDS　(case-based　reasoning-TBM　excavation　adaptive　evaluation　decision　system)　is　proposed,　and　the　TBM　tunneling　adaptability　evaluation　case　is　expressed　The　case-based　reasoning　method　and　modification　method　were　designed,　and　CBR-TBMEAEDS　was　developed.　The　system　can　be　used　to　evaluate　the　adaptability　of　TBM　to　the　constructed　case　library,　and　the　evaluation　results　are　consistent　with　the　actual　situation.