In order to study chromatographic retention time (RT) of aroma components from pineapple, molecular valence connectivity index (^mX^V_t), molecular shape index (ⁿK) and electrotopological state index (E_i) of 44 aroma components were calculated. ²X^V_p and ⁴X^V_c of the molecular valence connectivity indices, and ¹K and ²K of the molecular shape indices, E₈ and E₁₃ of the electrotopological state indices were optimized. The six parameters were used as input variables of neural network and the chromatographic retention time was used as output variable，and the 6∶3∶1 network structure was adopted and BP neural network method was used to establish a satisfying QSRR prediction model. The total correlation coefficient was 0.995. The predicted values by the model were in agreement those of the experiment values. A good nonlinear relationship between the chromatographic retention time and the six molecular structure parameters was found. The model could better elucidate the changing rule of chromatography retention time of the aroma components.