This study aims to investigate capability of the vibration prediction approaches, comprehensively. Field investigations were performed in a sandstone quarry. All the main conventional scaled distance equations were evaluated. A multivariate equation that contains blast design parameters was created by stepwise regression. A robust artificial neural network model was constructed. Effect of the additional parameters on success of the vibration estimation was examined. The success of the equations was evaluated considering the measurement distance. Evaluation of vibrations based on the measurement distance provided an opportunity to examine effectiveness of the equations that contains inelastic attenuation factor. Suitable error measures were investigated to examine the precision of vibration estimation. Both percentage errors and symmetric errors were found to be useful. Increase in the measurement distance was resulted in increase in prediction error. The classical scaled distance equations were found to be quite successful. The multivariate equation and artificial neural network model did not made better predictions than the scaled distance equations for long distance. The equations with inelastic attenuation formula do not have any advantage over classical scaled distance equations.