Abstract: The mechanism and affecting factors of the glass transition for polymers have been analyzed. The structural units of thirty-eight polyacrylates have been optimized and their quantum chemical descriptors have been obtained by DFT/6-31G(d) method. The calculated results indicate that the length of side chain, number of side chains, polarizability, dipole moment, EHOMO, heat capacity at constant volume, and thermal energy are the main factors affecting glass transition temperature (Tg). The regularity of Tg for polyacrylates is discussed by the pattern recognition method (PLS) with quantum chemical descriptors as features. The two classes of polymers with different Tg distribute in different regions. The quantitative relationship have been studied between these descriptors and Tg by stepwise regression and BP-ANN(back propagation artificial neural network) methods. The correlation coefficients between the predicted and experimental Tg for the two methods are 0.9753 and 0.9985, and the standard deviations are 18.42 and results 4.25, respectively.