Hydraulic conductivity curves (HCCs) are important parameters in land surface modeling. The general way for predicting HCC from soil water retention curve (SWRC) requires an additional input of the saturated hydraulic conductivity. The time-consuming in measurement and more importantly, the macro-effect near saturation, however, often result in difficulty and poor performance in predicting the conductivity. In this study, we provided a physically based method for predicting the HCC fully from SWRC requiring no additional parameters. This is achieved by applying an estimated conductivity (from SWRC) in the dry range as new matching point, in together with modifying the HCC model developed by Wang et al. (2018) that accounts for both capillarity and adsorption forces. Testing with a total of 159 soil samples yielded that the new model significantly improved the predictions of HCC, with R² being 0.74 and root mean value being 0.84 cm d⁻¹, nearly double and half of the value predicted with the input of the saturated hydraulic conductivity, respectively. The abrupt drop near saturation of the HCC model that provided by Wang et al. (2018) for soils with small n values close to 1, a parameter in shaping the SWRC, was also overcome by introducing a non-zero air-entry value.