Dynamization,　that　is,　increasing　interfragmentary　movement　(IFM)　by　reducing　fixation　stiffness　from　a　rigid　to　a　more　flexible　state,　has　been　successfully　used　in　clinical　practice　to　promote　fracture　healing.　However,　it　remains　unclear　how　dynamization　timing　and　degree　affect　bone　healing　of　different　fracture　types.　Finite　element　models　of　tibial　fractures　based　on　the　OTA/AO　classification　(Simple:　A1-Spiral,　A2-Oblique,　A3-Transverse;　Wedge:　B2-Spiral,　B3-Fragmented;　Complex:　C2-Segment,　C3-Irregular),　in　combination　with　fuzzy　logic-based　mechano-regulatory　tissue　differentiation　algorithms,　were　used　to　simulate　the　healing　process　when　dynamization　of　varied　degrees　(dynamization　coefficient　or　DC　=　0-0.9;　0.9　represents　90%　reduction　in　the　fixation　stiffness　relative　to　a　rigid　fixation)　were　applied　at　different　time　points　after　fracture.　The　fuzzy　logic-based　algorithms　have　been　validated　with　a　preclinical　animal　model.　The　results　showed　that　the　healing　responses　of　type　A　fractures　were　more　sensitive　to　the　changes　in　dynamization　degree　and　timing　comparing　with　type　B　or　C　fractures.　Additionally,　the　optimal　dynamization　regime　for　each　fracture　type　was　different.　For　type　A　fractures,　a　moderate　dynamization　degree　(e.g.,　DC　=　0.5)　applied　after　Week　1　promoted　the　recovery　of　biomechanical　integrity.　For　type　B　and　C　fractures,　the　effective　dynamization　included　a　greater　dynamization　degree　(DC　=　0.7)　applied　after　Week　2.　Our　results　further　demonstrated　that　the　fracture　morphology　affected　interfragmentary　strain　environments　within　the　callus,　leading　to　varied　healing　results　for　different　fracture　types.　These　results　suggest　that　the　effects　of　dynamization　are　highly　dependent　of　the　fracture　types.　Therefore,　specific　dynamization　strategies　should　be　chosen　for　different　fracture　types　to　achieve　optimal　healing　outcomes.