Background　and　Aims:　Breast　cancer　classify　into　four　molecular　subtypes:　Luminal　A,　Luminal　B,　HER2-overexpressing　(HER2),　and　triple-negative　(TNBC)　based　on　immunohistochemical　assessments.　The　multimodal　ultrasound　features　correlate　with　biological　biomarkers　and　molecular　subtypes,　facilitating　personalized,　precision-guided　treatment　strategies　for　patients.　In　this　study,　we　aimed　to　explore　the　differences　of　multimodal　ultrasound　features　generated　from　conventional　ultrasound　(CUS),　shear　wave　elastography　(SWE)　and　contrast-enhanced　ultrasound　(CEUS)　between　molecular　subtypes　of　breast　cancer,　investigate　the　value　of　prediction　model　of　breast　cancer　molecular　subtypes　based　on　multimodal　ultrasound　and　clinical　features.　Methods:　Breast　cancer　patients　who　visited　our　hospital　from　January　2023　to　June　2024　and　underwent　CUS,　SWE　and　CEUS　were　selected,　according　to　inclusion　criteria.　Based　on　the　selected　effective　feature　subset,　binary　prediction　models　of　features　of　CUS,　features　of　SWE,　features　of　CEUS　and　full　parameters　were　constructed　separately　for　the　four　breast　cancer　subtypes　Luminal　A,　Luminal　B,　HER2,　and　TNBC,　respectively.　Results:　There　were　ten　parameters　that　showed　significant　differences　between　molecular　subtypes　of　breast　cancer,　including　BI-RADS,　palpable　mass,　aspect　ratio,　maximum　diameter,　calcification,　heterogeneous　echogenicity,　irregular　shape,　standard　deviation　elastic　modulus　value　of　lesion,　time　of　appearance,　peak　intensity.　Full　parameter　models　had　highest　area　under　the　curve　(AUC)　values　in　every　test　set.　In　aggregate,　judging　from　the　values　of　accuracy,　precision,　recall,　F1　score　and　AUC,　models　used　features　selected　from　full　parameters　showed　better　prediction　results　than　those　used　features　selected　from　CUS,　SWE　and　CEUS　alone　(AUC:　Luminal　A,　0.81;　Luminal　B,　0.74;　HER2,　0.89;　TNBC,　0.78).　Conclusions:　In　conclusion,　multimodal　ultrasound　features　had　differences　between　molecular　subtypes　of　breast　cancer　and　models　based　on　multimodal　ultrasound　data　facilitated　the　prediction　of　molecular　subtypes.　©　The　Author(s)　2025.