This Study aims to develop an accurate and efficient methodology to predict the cross?anisotropic resilient modulus for unbound aggregates. [Methods] First,four unbound aggregates were collected and analyzed by the gradation test,compaction?density test,methylene blue test,percent fines content test,and aggregate imaging system test. Next,a new cross?anisotropic resilient modulus model was developed to characterize the stress?dependency and moisture?sensitivity of unbound aggregates. Subsequently,the laboratory rapid triaxial test was performed to determine the vertical,horizontal,and shear moduli of unbound aggregates with different gradations,stress levels,and moisture conditions. Finally,the R?squared values were used to evaluate the model's fitting accuracy. The JMP statistical software and multiple linear stepwise regression method were used to establish the correlation between unbound aggregate material properties and their cross?anisotropic resilient modulus model coefficients. [Findings] The unbound aggregates had a horizontal/vertical modulus ratio ranging from 0.3 to 0.6 and a shear/vertical modulus ratio ranging from 0.2 to 0.4. The intermediate?graded unbound aggregates had higher vertical,horizontal,and shear moduli than those of coarse? or fine?graded unbound aggregates. At different stress levels,the vertical,horizontal,and shear moduli of unbound aggregates decreased with the increased moisture content. [Conclusions] This study concluded that the new cross?anisotropic resilient modulus model accurately captured the influences of stress level and moisture conditions via the incorporation of matric suction and Henkerl stress terms,and the correlation of fitting coefficient was above 0.98. The multiple regression analysis indicated that the dry density,moisture content,methylene blue value,percent fines content,aggregate gradation,angularity,and shape are statistically significant variables affecting the cross?anisotropic resilient modulus model coefficients.