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We aimed to investigate the effects of mammary gland density and average glandular dose (AGD) on contrast-to-noise ratio (CNR) of breast-equivalent phantoms with different mammary gland/fat tissue ratios. Full-field digital-mammography breast X-rays were performed on breast-equivalent phantoms with three different mammary gland/fat tissue ratios (Phantom A [30/70], Phantom B [50/50], and Phantom C [70/30]) and seven thicknesses ranging from 10 mm to 70 mm. The prediction formula for the CNR was calculated by multivariate analysis and the effects of the various parameters on CNR were evaluated using a multiple regression analysis model. Higher CNR values were obtained with lower mammary gland/fat tissue ratios and lower phantom thicknesses. Variation in CNR among the three breast models was low (coefficient of variation, 3.4–8.7%) at lower phantom thicknesses (10–30 mm) and high (coefficient of variation, 10.5–16.8%) at higher phantom thickness (50–70 mm). CNR showed a strong negative correlation (r = -0.8989) with AGD across all three mammary gland ratios. A predictive formula for CNR using AGD and mammary gland density was developed. CNR can be predicted with high precision using AGD and mammary gland density. The predicted CNR could be used to measure the diagnostic reliability of mammography in breast cancer.