Soil slaking is a highly relevant property in erosion risk management and soil physics in general. Despite its importance and close relation with known soil chemical and physical properties such as soil organic carbon content, pH, sodium content, and soil aggregate stability, it is still underutilized mainly due to the lack of practical methodologies for measuring and understanding of its controlling factors. To facilitate and encourage its use in decision-making, infrared spectroscopy was tested as a proxy for its assessment. Different modelling approaches using soil reflectance values from the visible, near (Vis-NIR) and mid-infrared (MIR) regions of the electromagnetic spectra were employed to predict slaking index coefficient (SIa). The dataset had 146 samples with measured SIa, covering an important part of the agro-ecological variability of NSW, Australia. It was observed that the model's accuracy (20% used as an independent validation) increased as different regions of the spectra were considered. The results showed low predictability (R-2 0.45-0.54) using only the Vis-NIR region of the spectra, where only soil organic carbon (SOC) and Fe oxides spectral regions were identified as main predictors (similar to 2000- 2100 nm or 5000-4760 cm(-1) and similar to 700-900 nm or 14,280- 11,100 cm(-1)). As MIR regions were added, the modelling performance improved (R-2 0.51-0.76), where SOC and clay minerals related regions were also identified as important predictors (4700-4900 cm(-1), 3500-3700 cm(-1) or similar to 2000-2100 nm and similar to 2700-2850 nmrespectively). Since the uncertainty related to the models was relatively low(RMSE of similar to 1.0 slaking index units), it can be concluded that infrared spectroscopy can be used as a prospecting tool for predicting soil slaking. (C) 2021 Published by Elsevier B.V.