A　stochastic　micromechanical　framework　for　multiphase　composites　is　proposed　to　characterize　the　probabilistic　behaviors　of　effective　properties　of　composite　materials.　Based　on　our　previous　work,　the　deterministic　micromechanical　model　of　the　multiphase　composites　is　derived　by　introducing　the　strain　concentration　tensors.　By　modeling　the　volume　fractions　and　properties　of　constituents　as　stochastic,　we　extend　the　deterministic　framework　to　stochastic　to　incorporate　the　inherent　randomness　of　effective　properties　among　different　specimens.　A　new　simulation　framework,　consisting　of　univariate　approximation　for　multivariate　function,　Newton　interpolations,　and　Monte　Carlo　simulation,　is　developed　to　quantitatively　evaluate　the　stochastic　characteristics　of　the　effective　properties　of　composites.　Numerical　examples　including　limited　experimental　validations,　comparisons　with　existing　micromechanical　models,　and　the　Monte　Carlo　simulations　indicate　that　the　proposed　models　provide　an　accurate　and　computationally　efficient　framework　in　characterizing　the　effective　properties　of　multiphase　composites.　Finally,　the　effects　of　the　correlation　between　the　constituents＇　material　parameters　are　discussed　based　on　our　proposed　stochastic　micromechanical　model,　which　shows　that　the　negative　correlation　between　Young＇s　modulus　and　Poisson＇s　ratio　of　the　constituents　can　enhance　the　effective　properties　of　the　composites.