A three-layer back-propagation neural network model based on the non-linear relationship between the size of the SrTiO3 nanocrystalline and the technology factors, such as reaction time, reaction temperature, raw material adding amount of NaOH and SrCl2, and the rate of TiCl4/Hl, was established. Moreover, in order to accelerate the converging rate and avoid the non-converging situation, the momentum terms are introduced. Besides, the variable learning speed is adopted. At the same time, the input variables were pretreated by using the main component analysis firstly. And the results show that the improved back-propagation neural network model is very efficient for predication of the SrTiO3 nanocrystalline size.