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• Apply python to interface with plaxis software to simulate the embankment settlement for a case study in Australia. • Develope a GEP-based prediction model to estimate the settlement of ground improvement. • Conduct a parametric study to examine the effects of input variables on the settlement of the ground. • Optimize the design of CMC diameters and CMC spacings for specific ground conditions. This paper is going to present the advanced feature in Plaxis using remote scripting with Python wrapper. Python allows engineers to create Plaxis models, calculate construction phases, and plot the results automatically. The settlement estimation of a high embankment, supported by cement mixing columns (CMC), is presented as a case study. Approximately 500 models were created and analyzed within a few hours with different embankment heights, soft soil thickness, CMC spacing, and CMC diameter. This original database was used to develop a regression model using a Gene-expression programming (GEP) algorithm. The proposed GEP-based model with high accuracy could be applied to optimize the CMC design. In detail, the coefficient of correlation (R-value) of all phases is high and fluctuates from 0.967 to 0.976, while the mean absolute error of the model is lower than 0.009 m. The parametric study indicates that increasing the height of the fill embankment, the thickness of the peat layer, or the spacing between CMCs causes high settlement, while increasing the CMC diameter could significantly reduce the settlement of the embankment. The research results demonstrate that using Plaxis remote scripting and the GEP technique could help engineers run the numerical analysis much faster, leading to a more in-depth analysis to create better decision-making. [ABSTRACT FROM AUTHOR]