In this study, different AI approaches have been used to predict layered soil permeability, Linear Regression, Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Support Vector Machine (SVM). To find the model that best predicted the permeability of layered soil, the results underwent additional research and comparison because measuring soil permeability is a tedious and time-consuming process. This research builds upon prior investigations. The data sets literature (originated from an earlier in-lab investigation) containing 102 observations (70% and 30% of the remaining data were used for training and testing respectively) used to build up the models. It has been learned that AI is promising in presenting models that can measure layered soil permeability with a high degree of precision without requiring laboratory tests. The outcomes demonstrate that ANN is the best model for describing outcomes and for predicting the permeability coefficient of layered soil keq.