When industrial structures are constructed on soft ground, ground subsidence is occurred by problems of bearing capacity. To protect ground subsidence have to improve soft ground, and have to predict settlement estimation for reasonable construction. Artificial Neural Networks(ANN) is adopted for prediction of settlement of construction during the initial design. In the study, Artificial Neural Networks are applied to predict the settlement estimation of initial condition ground and ground improved by D.C.M method. Also, this study compares results of Artificial Neural Networks and results of continuum analysis using Mohr-Coulomb models. In result, settlements of initial condition ground decreased over 0.7 times. Also, by comparing ANN and continuum analysis, coefficient of determination was comparatively high value 0.79. Thought this study, it was confirmed that settlements of improvement ground is predicted using laboratory experiment data.