The　automatic　price　evaluation　is　an　important　and　challenging　issue　for　the　used　mobile　phone　recycling.　However,　due　to　complicated　relationships　between　attributes　and　price　as　well　as　insufficient　sample　data,　current　approaches　cannot　achieve　accurate　price　evaluation　for　the　used　mobile　phones,　which　significantly　reduce　the　efficiency　for　the　used　mobile　phone　recycling.　To　this　end,　a　tensor　based　approach　is　proposed　in　this　paper,　which　can　achieve　accurate　and　efficient　price　evaluation　for　used　mobile　phones.　In　the　proposed　approach,　first,　the　mutual　information　based　attributes　selection　mechanism　and　the　boxplot　based　sample　selection　mechanism　are　employed　to　select　the　most　relevant　attributes　and　suitable　price　samples　from　used　mobile　phone　dataset.　Then,　a　tensor　model　is　constructed　to　establish　multi-dimensional　relationships　between　selected　attributes　and　prices　of　used　mobile　phones.　Finally,　the　missing　values　in　the　constructed　tensor　model　is　completed　through　the　gradient　descent　and　CANDECOMP/PARAFAC　decomposition　algorithms.　The　completed　tensor　model　can　be　directly　used　for　the　price　evaluation　of　used　mobile　phones　based　on　their　attributes　without　further　calculation.　Based　on　the　real　price　dataset　of　used　mobile　phones,　the　experiments　indicate　that　the　proposed　approach　outperforms　most　of　current　approaches　for　the　price　evaluation　for　the　used　mobile　phones.