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Measuring the tempospatial variability of saturated hydraulic conductivity (Ks ) is time consuming, expensive, and encounters many uncertainties. This work aimed to develop a new model (REPM, Relative Effective Porosity Model) that estimates Ks from relative effective porosity (er ) and then compare it with a model (EPM, Effective Porosity Model) that estimates it from effective porosity (e ). The effective porosity (e ) is defined as the total porosity minus field capacity (FC), and the relative effective porosity (er ) is defined as effective porosity (e ) divided by FC. Both er and e can be estimated from FC and bulk density (Bd ). Data from 11 homogeneous texturalclass mean soils and several international and American soils were used to evaluate REPM and EPM. For the 11 texturalclass mean soils, log (Ks ) was highly correlated to log (er ) as well as to log (e ). For the international soils, log (Ks ) was highly correlated to log (er ) (r 2 = 0.77), but the correlation was less pronounced between log (Ks ) and log ( e ) (r 2 = 0.58). The saturated hydraulic conductivity of soils from an international database was more accurately predicted by REPM (RMSE of 539 cm d 1 ) than by EPM (RMSE of 733 cmd 1 ), while both of them performed as well for American soils. The slope and the intercept of REPM and the slope of EPM were independent of soil. These results suggest that our new model gives reasonable estimates of Ks for different soils.