Optimal　process　parameters　are　the　foundation　for　obtaining　high-quality　cladding　coatings.　However,　the　optimization　of　process　parameters　and　their　interactions　affecting　the　coating　has　always　been　a　challenge　in　the　application　of　High-speed　Laser　Cladding　(HLC)　technology.　This　study,　utilizing　experimental　data　from　Central　Composite　Design　(CCD),　the　application　of　response　surface　methodology　(RSM)　and　non-dominated　sorting　genetic　II　(NSGA-II)　algorithms　for　process　parameter　optimization　in　high-speed　laser　cladding　of　FeCrNiMo0.75　coating　was　thoroughly　investigated,　and　comparative　experimental　validation　of　the　optimization　results　was　performed.　The　results　showed　that　the　aspect　ratio　of　the　coating　and　microhardness　was　a　mutually　restrictive　relationship.　Both　methods　improved　the　response　targets　after　optimization,　but　the　focus　of　the　optimization　results　differed.　The　aspect　ratio　optimization　result　of　RSM　was　better　than　that　of　NSGA-II,　while　the　micro-　hardness　optimization　result　of　NSGA-II　was　superior　to　RSM.　Cladding　trials　using　process　parameters　optimized　by　RSM　showed　that　the　actual　coating　hardness　was　261.7　HV0.1,　with　a　prediction　error　of　3.54　%,　and　the　actual　aspect　ratio　was　8.1945,　with　a　prediction　error　of　2.84　%.　Additionally,　cladding　trials　using　process　parameters　optimized　by　NSGA-II　showed　an　actual　coating　hardness　of　318.8　HV0.1,　with　a　prediction　error　of　2.70　%,　and　an　actual　aspect　ratio　of　6.9452,　with　a　prediction　error　of　1.68　%.　This　offers　valuable　insights　for　optimizing　process　parameters　and　enhances　the　practical　application　of　high-speed　laser　cladding.