To predict the standard absolute entropies of gaseous organic compounds, the variable molecular connectivity index ((m)chi') and Ring parameter (H), based on adjacency matrix of molecular graphs, variable atomic valence connectivity index (delta(i)'), and the numbers of atomic chains (cycles) of molecule n(i)(R) were proposed. The optimal values of parameters b, c, m(i), and y included in the definition of delta(i)', and m chi' can be found by using an optimization method. When b = 1.3, c = 0.91, and y = 0.22, a good four-parameter model can be constructed from H and (m)chi' by using the best subsets regression analysis method for the standard absolute entropies of gaseous organic compounds. The correlation coefficient (r), standard error (s), and average absolute deviation (AAD) of the multivariate linear regression (MLR) model are 0.9988, 8.16 J K-1 mol(-1), and 6.13 J K-1 mol(-1), respectively, for the 726 gaseous organic compounds (training set). The AAD of predicted values of the standard absolute entropy of another 364 gaseous organic compounds (test set) is 6.14 J K-1 mol(-1) for the MLR model. The results show that the MLR method can provide an accurate model for the prediction of the standard absolute entropies of gaseous organic compounds.