With the rising needs of better prediction of the load-displacement performance of grouted anchors in an era of developing large-scale underground infrastructures, the existing methods in literature lack an accurate analytical model for the real-life projects or rigorous understanding of the parameters such as grouting pressures.This paper proposes FastICA-MARS as a novel data-driven approach for the prediction of the load-displacement performance of uplift-resisting grouted anchors.The hybrid and data-driven FastICA-MARS approach integrates the multi-variate adaptive regression splines(MARS)technique with the FastICA algorithm which is for Independent Component Analysis(ICA).A database of 4315 observations for 479 different anchors from 7 different projects is established.The database is then used to train, validate and compare the FastICA-MARS approach with the classical MARS approach.The developed FastICA-MARS model can provide more accurate predictions than MARS.Moreover, the developed FastICA-MARS model is easy to interpret since the evaluation of the parameter importance of the independent components can be conducted along with the considerations of the correlations with the original variables.It is noteworthy to point out that the grouting pressures play a central role in the proposed model, which is considered of paramount importance in engineering practices but has not been properly taken into account in any prior analytical or empirical predictive models for the load-displacement relationships.