The soil hydraulic properties, coefficient of permeability and storage are essential data to predict the behavior of groundwater. Pumping tests are usually performed to determine these properties. In this paper, a new approach to evaluate soil hydraulic properties from drawdown curves which are obtained by pumping tests has been developed. In our proposed method the pattern-matching capability of a neural network is used. The neural network is trained to recognize patterns of drawdown data as input and corresponding hydraulic properties in the confined aquifer as output. The trained network produces output of hydraulic properties when it receives pumping test data as the input patterns. Drawdown data which are observed in an anisotropic confined aquifer are used to evaluate availability of our proposed method.