In recent years, soft computing technology has been used as an alternative statistical tool. The artificial neural network (ANN) is used to develop predictive models to estimate the required parameters. In this study, a neural network model for predicting rock properties was established by using some of the drilling parameters (pressure, thrust, bit diameter, penetration) and the resulting sound level during the impact drilling process. Data generated in the laboratory was used for the development of neural network models that predict rock properties such as uniaxial compressive strength, wear resistance, tensile strength, and Schmidt rebound number. The models were tested with various predictive performance indicators and the results show that the artificial neural network model is suitable for the prediction of rock properties.