Well-known analytical equations for predicting permeability are generally reported to overestimate this important property of porous media. In this work, more robust models developed from statistical (MVR) and Artificial Neural Network (ANN) methods utilized additional particle characteristics ('fines ratio' (x 50 /x 10 ) and particle shape) that are not found in traditional analytical equations. Using data from experiments and literature, model performance analyses with average absolute error (AAE) showed error of ~40% for the analytical models (Kozeny-Carman and HappelBrenner). This error reduces to 9% with ANN model. This work establishes superiority of the new models, using experiments and mathematical techniques.