Selection　of　advanced　manufacturing　technologies　(AMTs)　is　an　important　yet　complex　decision　which　requires　careful　consideration　of　various　performance　criteria.　This　paper　proposes　the　use　of　data　envelopment　analysis　(DEA)　with　double　frontiers　for　the　selection　of　AMTs,　which　considers　not　only　the　best　(optimistic),　but　also　the　worst　(pessimistic)　relative　efficiencies　of　each　AMT.　Compared　with　the　traditional　DEA,　the　DEA　approach　with　double　frontiers　can　identify　the　best　AMT　correctly　and　easily　without　the　need　to　impose　any　weight　restriction　or　the　need　to　calculate　the　cross-efficiency　matrix,　which　requires　a　large　number　of　computations　and　may　also　result　in　inconsistent　conclusions　by　aggressive　and　benevolent　cross-efficiency　models.　Four　numerical　examples　are　examined　using　the　DEA　approach　with　double　frontiers　to　illustrate　its　simplicity　and　usefulness　in　AMT　selection　and　justification.