Nd:　YLF　laser　beam　machining　(LBM)　process　has　a　great　potential　to　manufacture　intricate　shaped　microproducts　with　its　unique　characteristics.　Continuous　improvement　(CI)　effort　for　LBM　process　is　usually　realised　by　response　surface　methodology,　which　is　an　important　tool　in　Design　of　Six　Sigma.　However,　when　determining　the　optimal　machining　parameters　in　CI　for　LBM　process,　model　parameter　uncertainty　is　typically　neglected.　Performing　worst　case　analysis　in　CI,　this　paper　presents　a　new　loss　function　method　that　takes　model　parameter　uncertainty　into　account　via　Bayesian　credible　region.　Unlike　existing　CI　methods　in　LBM　process,　the　proposed　Bayesian　probabilistic　approach　is　based　on　seemingly　unrelated　regression　which　can　produce　more　precise　estimations　of　the　model　parameters　than　ordinary　least　squares　in　correlated　multiple　responses　problems.　An　Nd:　YLF　laser　beam　micro-drilling　process　is　used　to　demonstrate　the　effectiveness　of　the　proposed　approach.　The　comparison　results　show　that　micro-holes　produced　by　the　proposed　approach　have　better　quality　than　those　of　existing　approaches　in　terms　of　robustness　and　process　capability.