Kumar, S.Sarkar, R.Nainegali, L.2026-02-032025European Journal of Environmental and Civil Engineering, 2025, 29, 15, pp. 3443-347619648189https://doi.org/10.1080/19648189.2025.2523880https://idr.nitk.ac.in/handle/123456789/20680Failures of vertical piles are common under earthquake loading, especially in laterally spreading ground conditions. Performance is supposed to be better for batter piles due to their higher lateral load-carrying capacity. However, the framework of the design of batter piles is still not available for laterally spreading ground for different degrees of batter, considering the associated uncertainties. This paper investigates the effects of uncertainties on the performance of batter piles in laterally spreading ground. The beam on nonlinear Winkler foundation (BNWF) approach was considered for modelling the soil-pile systems. Nonlinear analyses were carried out for cosine-shaped ground deformation profiles. Effects of the uncertainty of critical parameters such as ground slope, relative density and thickness of the liquefying layer, batter angle, and slenderness ratio of the piles were investigated through a factorial design approach. A central composite design approach was adopted to investigate the curvature effects of the uncertain parameters. It was observed that the negative batter piles perform significantly better than their counterparts of vertical and positive batter piles. This study proposes prediction models for maximum bending moment and pile head displacement for piles with different batter angles, considering a three-layered laterally spreading ground. © 2025 Informa UK Limited, trading as Taylor & Francis Group.ForecastingNonlinear analysisPile drivingPrediction modelsUncertainty analysisBatter anglesBatter pilesBeam on nonlinear winkl foundation approachLateral spreadingLaterally spreading groundPerformancePrediction modellingUncertaintyVertical pilesWinkler foundationsPilesEffects of uncertainty of critical parameters on performance of piles with different batter angles in laterally spreading ground: development of prediction models