The behavior of the concrete piles subjected to lateral load depends on subsoil conditions, sectional properties of the pile, and boundary conditions of the pile at the top and bottom. This paper investigates the application of artificial neural networks (ANN) to predict max deflection, max bending moment, and max soil reaction of laterally loaded concrete piles on various soil conditions. The data used in the ANN model consists of various inputs such as dimensions of the pile, material properties, loads, and soil properties. The ANN models are trained using 70% of the data, and tested and validated using the remaining 30%. The data required for ANN training was generated after numerical analysis using the Subgrade Reaction Approach on discrete concrete piles. Numerical analysis of the pile model using the subgrade approach is confirmed with manual calculation as per IS: 2911(Part 1/Sec 4)-2010. This paper investigates the capability/usefulness of ANN to monitor the response of a laterally loaded concrete pile for different soil conditions. From observing results, show very negligible deviation between computed results by the Subgrade approach and ANN results.