The　potential　to　provide　improved　performance　for　advanced　composites　through　the　addition　of　multi-walled　carbon　nanotubes　(MWCNTs)　to　carbon　fiber　composites　is　of　interest　in　several　applications.　To　investigate　performance　four　types　of　composite　specimens　with　different　off-axis　angles　were　subjected　to　progressive　tensile　loading.　The　results　show　that　MWCNTs　can　improve　the　bearing　capacity　of　the　composite　and　the　off-axis　orientation　angle　can　enhance　the　toughness　of　the　composite.　During　loading　acoustic　emission　(AE)　signals　were　collected　and　they　were　post-processed　using　cluster　analysis　based　on　a　Fuzzy　C-Means　algorithm.　The　analysis　of　the　AE　signals　shows　that　data　can　be　divided　into　categories　which　correlate　with　three　damage　modes:　matrix　cracking,　fiber　debonding　and　fiber　breakage.　The　AE　peak　frequency　characteristics　of　each　damage　mode　were　identified.　Additional　characterization　was　provided　by　using　micro-computed　tomography　(Micro-CT)　during　the　progressive　tensile　loading　process.　The　CT　images　visualize　damage　location　and　evolution　in　the　composites　and　data　exhibit　good　correlations　with　the　AE　data　for　defects　predication.　The　combination　of　AE　and　micro-CT　technology　were　shown　to　effectively　characterize　damage　evolution　of　the　composites,　and　such　data　can　potentially　serve　as　a　reference　for　the　structural　health　monitoring　of　these　composites　when　used　in　structures.