Predicts solvent accessibility of amino acids using an optimized neural network algorithm. NETASA provides accuracy values, which are comparable or better than other methods of ASA (accessible surface area) prediction. Prediction in two and three state classification systems with several thresholds are provided. This prediction method achieved the accuracy level up to 90% for training and 88% for test data sets. NETASA also includes a linear activation function and some changes in the training procedure.