In　this　study,　the　method　of　magnetic　Barkhausenn　noise　(MBN)　and　tangential　magnetic　field　(TMF)　was　employed　for　achieving　simultaneous,　quantitative　prediction　of　residual　stress　and　surface　hardness　in　box-shape　deep　drawn　parts　of　SPCC　steel.　Bi-directional　MBN　and　TMF　signals,　profiles　of　surface　hardness　and　residual　stress　were　experimentally　measured.　Pearson　correlation　analysis　results　show　that　the　averaged　amplitude　of　MBN　in　one　magnetization　cycle　and　Root　mean　square　of　MBN　signal　demonstrates　approximate　linear　dependency　on　residual　stress　(or　surface　hardness)　in　both　the　measured　directions.　Three-layer　BP　models　are　established　after　input　nodes　screening　and　optimization　of　neurons＇　number　in　the　middle　hidden　layer.　BP　models　are　marked　corresponding　to　scanning　or　magnetization　directions.　For　each　direction,　two　independent　models　are　established　and　they　are　combined　to　use　for　realizing　high　accuracy　and　simultaneous　evaluation　of　the　residual　stress　and　surface　hardness.