Birds　are　dominant　creatures　that　produce　abundant　sounds　in　urban　forest　ecosystems,　and　birdsongs　are　a　desired　soundscape　to　reduce　noise　pollution　in　biophilic　cities.　The　aim　of　this　study　was　to　explore　the　impact　of　soundscape　drivers　on　perceived　birdsongs　and　to　model　the　associated　drivers.　Questionnaires　and　acoustic　measurements　of　biophony　and　birdsongs　were　conducted　at　41　observation　sites　in　three　urban　forest　locations　in　Vancouver,　Canada.　Pearson＇s　correlations　were　then　used　to　analyze　relationships　between　the　soundscape　drivers.　Potential　soundscape　drivers　were　modeled　using　template　matching　(TM)　and　back　propagation　neural　network　(BP　neural　network).　Findings　suggest　that　there　is　an　interaction　between　perceived　birdsongs　and　the　pleasantness　of　perceived　birdsongs　(PPB),　eventfulness　of　perceived　birdsongs　(EPB),　and　number　types　of　perceived　birdsongs　(NTP).　Results　also　show　that　high　frequency　contents　have　an　effect　on　perceived　birdsongs　in　urban　forests.　We　established　a　perceived　birdsongs　model　(PBM)　that　effectively　simulates　the　process　from　soundscape　information　to　perceived　birdsongs　in　urban　forests,　and　the　methodology　developed　in　this　study　could　be　useful　for　conducting　soundscape　assessment　and　promoting　soundscape　conservation　in　other　urban　forests.　©　2020　Elsevier　Ltd