Background　To　develop　a　predictive　model　using　baseline　imaging　of　morphology　and　radiomics　derived　from　intravoxel　incoherent　motion　diffusion-weighted　imaging　(IVIM-DWI)　to　determine　the　pathologic　complete　response　(pCR)　to　neoadjuvant　chemotherapy　(NACT)　in　breast　cancer　patients.Methods　A　total　of　265　patients　who　underwent　3.0　T　MRI　scans　before　NACT　were　examined.　Among　them,　113　female　patients　with　stage　II-III　breast　cancer　were　included.　The　training　data　set　consisted　of　79　patients　(31/48=pCR/Non-PCR,　npCR),　while　the　remaining　34　cases　formed　the　validation　cohort　(13/21=pCR/npCR).　Radiomics　and　conventional　magnetic　resonance　imaging　features　analysis　were　performed.　To　build　a　nomogram　model　that　integrates　the　radiomics　signature　and　conventional　imaging,　a　logistic　regression　method　was　employed.　The　performance　evaluation　of　the　nomogram　involved　the　area　under　the　receiver　operating　characteristic　curve　(AUC),　a　decision　curve　analysis,　and　the　calibration　slope.Results　In　an　assessment　for　predicting　pCR,　the　radiomics　model　displayed　an　AUC　of　0.778　and　0.703　for　the　training　and　testing　cohorts,　respectively.　Conversely,　the　morphology　model　exhibited　an　AUC　of　0.721　and　0.795　for　the　training　and　testing　cohorts,　respectively.　The　nomogram　displayed　superior　predictive　discrimination　with　an　AUC　of　0.862　for　the　training　cohort　and　0.861　for　the　testing　cohort.　Decision　curve　analyses　indicated　that　the　nomogram　provided　the　highest　clinical　net　benefit.Conclusion　Performing　a　nomogram　consisting　of　integrated　morphology　and　radiomics　assessment　using　IVIM-DWI　before　NACT　enables　effective　prediction　of　pCR　in　breast　cancer.　This　predictive　model　therefore　can　facilitate　medical　professionals　in　making　individualized　treatment　decisions.