Creating more personalized breast cancer risk prediction models would enhance the benefits and limit the harms of routine breast cancer screening. This study aims to evaluate the performance of multi-feature image risk score (radiomics) models in a large population-based cohort; determine whether image-based scores predict breast cancer risk independently of clinical and genetic predictors; and transfer the best image-based algorithm from 2D to 3D images.