The　combination　of　multifunctional　micromagnetic　testing　and　neural　network-based　prediction　models　is　a　promising　way　of　nondestructive　and　quantitative　measurement　of　steel　surface　hardness.　Current　studies　mainly　focused　on　improving　the　prediction　accuracy　of　intelligent　models,　but　the　unavoidable　and　random　uncertainties　related　to　instruments　were　seldom　explored.　The　robustness　of　the　prediction　model　considering　the　repeatability　of　instruments　was　seldom　discussed.　In　this　work,　a　self-developed　multifunctional　micromagnetic　instrument　was　employed　to　perform　the　repeatability　test　with　Cr12MoV　steel.　The　repeatability　of　the　instrument　in　measuring　multiple　magnetic　features　under　both　static　and　dynamic　conditions　was　evaluated.　The　magnetic　features　for　establishing　the　prediction　model　were　selected　based　on　the　consideration　of　both　the　repeatability　of　the　instrument　and　the　ability　of　magnetic　features　in　surface　hardness　evaluation.　To　improve　the　robustness　of　the　model　in　surface　hardness　prediction,　a　modelling　strategy　considering　the　repeatability　of　the　instrument　was　proposed.　Through　removing　partial　magnetic　features　with　higher　mean　impact　values　from　input　nodes,　robust　evaluation　of　surface　hardness　in　Cr12MoV　steel　was　realized　with　the　multifunctional　micromagnetic　instrument.