Surface displacements are routinely monitored at multiple points during slope excavation. The monitoring data reveals the safety status of the slope under current loading conditions. They can be used to enhance the prediction of the future performance of the slope by reducing the uncertainties of the prediction model and its model parameters. In a multistage excavation, the observed displacements in the current stage can be used to update the prediction of the displacements in subsequent stages. Besides, due to the spatial correlation of the slope parameters, the prediction of the displacement at one location can also be updated using the monitored displacements at adjacent locations. This study aims to develop a multistep updating method to enhance the prediction of the future performance of the slope using time-series monitoring data at multiple points. This method integrates the theoretical computational model with observational evidence. It considers the inherent uncertainty of the slope, model uncertainty and measurement uncertainty. With more monitoring information being incorporated, the prediction becomes closer to the actual performance of the slope. A case study of a multistage excavation of an extremely high rock slope in south-west China is presented for illustration.CITATION:Li, X Y and Zhang, L M, 2014. Better prediction of performance of a slope using time-series monitoring data at multiple points in a multistep excavation, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 183-188 (The Australasian Institute of Mining and Metallurgy: Melbourne).