This study aims to accurately predict the flexural strength (FS) of glass fiber reinforced concrete (GFRC) using advanced machine learning (ML) techniques. A novel algorithm, tree structured parzen estimator based extreme gradient boosting (TPE-XGB), is proposed by integrating Bayesian optimization (TPE) for automated hyperparameter tuning with the predictive strength of XGB. In addition to TPE-XGB, other ML algorithms includi...