Research　of　protein　3D　structures　plays　a　key　role　in　molecular　biology,　cell　biology,　biomedicine,　and　drug　design.　The　protein　fold　type　reflects　the　topological　pattern　of　the　structure＇s　core.　Fold　recognition　is　an　important　method　in　protein　sequence-structure　research.　On　the　53　fold　types　which　have　more　than　10　samples　in　LIFCA　were　selected.　The　functional　domain　composition　is　introduced　to　predict　the　fold　types　of　a　protein　or　a　domain.　After　testing　9　211　proteins　with　less　than　95%　sequence　identity　from　the　Astral　1.65　database,　the　average　sensitivity,　specificity　and　Matthew＇s　correlation　coefficient　(MCC)　of　the　53　fold　types　were　found　to　be　96.42%,　99.91%　and　0.91,　respectively.　The　result　indicates　that　using　the　functional　domain　composition　to　represent　a　protein　is　very　promising　for　protein　fold　recognition.　And　though　based　on　simple　classification　rules,　LIFCA　can　concentrate　the　functional　features　of　proteins,　reflecting　the　corresponding　relation　between　structure　and　function.