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This study presented the performance of the gradient boosted regression trees (GBRT) model for predicting the axial load capacity (ALC) of the cold-formed steel semi-oval hollow section (CFS-SOHS) columns. A total of 219 datasets were carefully collected from previous publications including experimental and numerical results, which were used to develop the GBRT model. Of these, 209 datasets were used for training, while 10 datasets were used for testing. The results obtained from the GBRT model were compared with two existing formulas based on the statistical metrics (). The statistical metrics from the GBRT model and have been the best-predicting to the ALC of the CFS-SOHS column. Finally, a new graphical user interface \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts …