A novel quantitative structure-property relationship (QSPR) modelling method developed for predicting the ignition delay time of 31 hypergolic imidazolium ionic liquid derivatives which is WFNA (white fuming nitric acid) used as their oxidizer. Chemical structures of these ILs were encoded into several sets of molecular descriptors, representing various physical and chemical properties of these molecules. A total number of 1447 molecular descriptor with different types (e.g., constitutional, functional group counts, and geometrical descriptors) were selected and calculated, then the combination of stepwise and best subset regression approaches was used to determine the molecular descriptors which have significant effects on ignition delay time of hypergolic imidazolium ionic liquid derivatives, finally the response plot of PLS regression approach applied to the selected descriptors, to choose the best number of them. The final derived model displayed a good predictive ability arising from the determination coefficient corresponding to the leave one out cross validation technique (R-2=0.9925 and QLOO2=0.9834). The predictive power of the proposed method is evaluated using several different techniques and this method can be used as a reliable tool for designing novel hypergolic ILs.