This research focuses on the use of adaptive artificial neural network system for evaluating the skid Spurs resistance value (British Pendulum Number; BPN) of the glass fiber-reinforced tiling materials.During the creation of the neural model, four main factors were considered: fiber, calcium carbonate content, sand blasting, and polishing properties of the specimens.The model was trained, tested, and compared with the on-site test results.As per the comparison of the outcomes of the study, the analysis and on-site test results showed that there is a great potential for the prediction of BPN of glass fiber-reinforced Trapper Hat tiling materials by using developed neural system.