In　Software　Defined　Network　(SDN)　environment,　controller　has　to　compute　and　install　routing　strategy　for　each　new　flow,　leading　to　a　lot　of　computation　and　communication　burden　in　both　controller　and　data　planes.　In　this　background,　intelligent　routing　pre-design　mechanism　is　regarded　to　be　an　important　approach　for　routing　efficiency　enhancement.　This　paper　investigates　and　proposes　efficient　SDN　routing　pre-design　solution　in　three　aspects:　flow　feature　extraction,　requirement　prediction　and　route　selection.　First,　we　analyze　and　extract　data　packet　and　association　features　from　user　history　data,　apply　these　features　into　semi-supervised　clustering　algorithm　for　efficient　data　classification,　analysis　and　feature　extraction.　After　that,　flow　service　requirement　could　be　predicted　through　extraction　of　user,　flow　and　data　plane　load　features　and　implementation　of　supervised　classification　algorithm.　Furthermore,　we　propose　corresponding　handling　strategies　related　to　data　plane　topology,　flow　forwarding　and　multi-constraint　weight　assignment,　and　proposes　personalized　routing　selection　mechanism.