Probabilistic neural network is applied to facilitate slope stability estimation by making use of data mining technique and intelligent system. Data mining can draw attention to meaningful structures in the archives of such slope stability data. The soil mechanical characteristics and the slope shape with significant influence on slope stability are used to train and test the neural network. Validation is performed to show the efficiency of probabilistic neural network for estimation of slope stability. The simulation results show that probabilistic neural network model generate higher predicting precision than the conventional linear regression

limit equilibrium method and maximum likelihood estimation.