Case　retrieval,　case　reuse　and　case　retention　are　critical　to　the　reasoning　performance　of　the　traditional　case-based　reasoning　(CBR)　model.　In　this　paper,　the　integrated　use　of　template　reduction　technology　(TR),　genetic　algorithms　(GA),　nearest　neighbor　(NN)　rules　and　group　decision-making　(GDM)　establishes　the　CBR-GDM　model.　First,　the　TR　method　of　the　case　base　is　introduced.　Then,　an　attribute　weights　optimization　using　GA　is　discussed　in　the　case　retrieval　phase.　After　that,　a　case　reuse　method　is　carried　out　with　NN　and　GDM.　Finally,　10　data　sets　from　UCI　are　used　to　carry　out　a　comparison　experiment　by　5-fold　cross-validation.　The　classification　accuracy　rate　and　the　classification　efficiency　are　analyzed　under　the　small　samples,　before　and　after　the　data　reduction.　The　results　show　that,　combined　with　TR,　GA　and　GDM,　the　pattern　classification　performance　by　CBR　can　be　improved.