Quantitative structure spectroscopy relationships (QSSRs) are systematically studied for carbon-13 nuclear magnetic resonance ((13)C NMR) spectroscopic simulation of steroid compounds. Both the atomic electronegativity interaction vector (AEIV) and the atomic hybridization state index (AHSI) are used for the expression of local chemical microenvironment and atomic hybridization state of 4434 resonance carbon atoms in 203 steroid molecules. A multiple linear regression (MLR) model is built after screening some insignificant parameters with the stepwise multiple regression (SMR) technique. Correlation coefficients of the developed model are R(cum)(2)=0.9341 and Q(LOO)(2)=0.9336 for classical estimation of molecular modeling and the cross-validation with leave-one-out (LOO) procedures, respectively, primarily indicating that the MLR model has good modeling stability and prediction ability. Furthermore, the superior performance of the MLR model is tested by the leave-33%-out (L33%O) cross-validation method, where the mean correlation coefficients of three test sets are Q(2)=0.9310 and Q(ext)(2)=0.9196 for both internal and external sets. In conclusion, AEIV and AHSI descriptors can be used for estimating and predicting (13)C NMR chemical shifts of steroids.