In　recent　years,　mergers　and　acquisitions　(MA)　have　been　frequent,　but　the　failure　rate　of　MA　has　remained　high　in　reality.　In　order　to　reduce　the　MA　failure　rate,　a　key　step　is　to　achieve　an　effective　MA　matching　which　can　help　integrate　enterprise　resources　and　can　make　companies　bigger　and　stronger.　Given　the　risk　of　poor　MA　matching　decisions,　it　is　important　to　consider　both　the　rational　and　irrational　behavior　of　decision-makers.　This　study　developed　a　MA　matching　method　that　considers　irrational　behavior　from　a　DEA-based　performance　perspective.　In　this　method,　the　MA　party　evaluates　the　other　party　with　itself　as　the　reference　point.　However,　the　approach　also　draws　on　the　idea　of　cross-efficiency　modeling.　In　this　approach,　we　construct　a　data　envelopment　analysis　(DEA)　model　that　has　a　prospect　value　as　the　secondary　optimization　goal.　This　generates　index　weights　to　further　determine　decision　weights.　Then,　the　value　and　decision　weights　are　aggregated　into　a　prospect　value,　which　is　used　to　assess　the　degree　of　satisfactory　matching　to　optimize　the　two-sided　MA　matching.　We　then　provide　an　example　to　illustrate　the　feasibility　and　effectiveness　of　two-side　MA　matching.　This　method　can　be　applied　to　third-party　platforms　to　provide　matching　recommendation　services　for　participating　MA　companies.　©　2013　IEEE.