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Motivation: This study presents a novel nonlinear model which can predict 10‐year carotid ultrasound image‐based phenotypes by fusing nine traditional cardiovascular risk factors (ethnicity, gender, age, artery type, body mass index, hemoglobin A1c, hypertension, low‐density lipoprotein, and smoking) with five types of carotid automated image phenotypes (three types of carotid intima‐media thickness (IMT), wall variability, and total plaque area). Methodology: Two‐step process was adapted: First, five baseline carotid image‐based phenotypes were automatically measured using AtheroEdge™ (AtheroPoint™, CA, USA) system by two operators (novice and experienced) and an expert. Second, based on the annual progression rates of cIMT due to nine traditional cardiovascular risk factors, a novel nonlinear model was adapted for 10‐year predictions of carotid phenotypes. Results: Institute review board (IRB) approved 204 Japanese patients' left/right common carotid artery (407 ultrasound scans) was collected with a mean age of 69 ± 11 years. Age and hemoglobin were reported to have a high influence on the 10‐year carotid phenotypes. Mean correlation coefficient (CC) between 10‐year carotid image‐based phenotype and age was improved by 39.35% in males and 25.38% in females. The area under the curves for the 10‐year measurements of five phenotypes IMTave10yr, IMTmax10yr, IMTmin10yr, IMTV10yr, and TPA10yr were 0.96, 0.94, 0.90, 1.0, and 1.0. Inter‐operator variability between two operators showed significant CC (P < 0.0001). Conclusions: A nonlinear model was developed and validated by fusing nine conventional CV risk factors with current carotid image‐based phenotypes for predicting the 10‐year carotid ultrasound image‐based phenotypes which may be used risk assessment. [ABSTRACT FROM AUTHOR]