This　article　proposes　a　new　data　envelopment　analysis　(DEA)-based　approach　to　deal　with　mergers　and　acquisitions　(M&As)　matching.　To　derive　reliable　matching　degrees　between　bidder　and　target　firms,　we　consider　both　technical　efficiency　and　scale　efficiency.　Specifically,　an　inverse　DEA　model　is　developed　for　measuring　the　technical　efficiency,　while　a　conventional　DEA　model　is　employed　to　identify　the　return　of　scale　of　the　merged　decision-making　units　(DMUs).　Then,　an　optimization　model　is　formulated　to　generate　matching　results　to　improve　DMUs＇　performance.　An　empirical　study　of　M&As　matching　Turkish　energy　firms　is　examined　to　illustrate　the　proposed　approach.　This　study　shows　that　both　technical　efficiency　and　scale　efficiency　have　impacts　on　M&As　matching　practices.