In　this　paper,　a　new　approach　to　generate　decision　tree　from　those　examples　with　interval-valued　attributes　is　presented　and　then　rule　matching　is　made.　Considering　that　the　interval　values　of　the　same　attribute　of　all　examples　probably　fall　into　certain　distributing　rule　so　as　to　form　some　center　points,　we　cluster　the　interval-valued　attributes　of　all　examples　by　using　the　algorithm　of　FCCID　(Fuzzy　C-mean　Clustering　for　Interval-valued　Data).　Consequently,　the　attributes　represented　by　interval　data　are　transformed　into　those　represented　by　fuzzy　degree　of　membership.　On　the　basis　of　that,　the　fuzzy　ID3　algorithm　is　adopted　to　generate　a　decision　tree　for　rule　matching.