The　aim　of　the　present　study　was　to　optimize　a　formulation　of　the　vat-polymerization　binder　of　3D　printing　ceramic　slurry　using　a　D-optimal　mixture　experimental　design.　The　selected　methodology　was　based　on　an　extreme　vertices　approach　with　13　combinations,　selecting　three　types　of　resin　monomers　(TMPTA,　NPG2PODA,　HDDA)　and　one　type　of　plasticizer　(TXIB)　as　independent　variables,　while　mechanical　properties　(including　tensile　strength　and　elongation　at　break),　volume　shrinkage,　viscosity,　and　curing　depth　were　considered　as　response　variables.　The　experimental　data　were　analyzed　to　generate　statistical　models　and　response　surfaces　for　analyzing　the　effects　of　component　fractions　on　individual　responses.　Analysis　of　variance　was　performed.　This　method　was　applied　to　predict　the　optimal　formulation.　Based　on　the　DoE　results,　the　mixture　of　resins　and　plasticizer　with　an　optimized　composition　ratio　after　curing　showed　better　mechanical　properties,　lower　volume　shrinkage,　lower　viscosity,　and　an　appropriate　curing　depth.　Furthermore,　a　ceramic　slurry　containing　55　vol%　Al2O3　was　prepared　to　evaluate　the　printability　of　the　optimized　mixture.　The　relatively　dense　ceramic　parts　and　smooth　surface　were　successfully　manufactured　after　de-binding　and　sintering.　Our　findings　demonstrate　the　efficiency,　reliability,　and　feasibility　of　the　D-optimal　mixture　experimental　design　in　modeling,　predicting,　and　optimizing　the　formulation　of　the　TMPTA/NPG2PODA/HDDA/TXIB　composite.　Overall,　this　study　can　be　helpful　in　designing　experiments　and　optimizing　the　vat-polymerization　of　3D　printing　ceramic　slurry.