The knowledge of saturated soil hydraulic conductivity (K_s) is of major importance in modern agriculture and in various modeling applications.  Measurements of K_s are time consuming and not an easy tasked. This parameter has been determined for only few soils in surveys and showed high spatial variation.  Therefore, its prediction from other simpler soil data is an acceptable approach to characterize a large area or to be utilized in modeling. Pedotransfer functions (PTF) have gained recognition in recent years as an approach  to translate simple and easily determined soil characteristics into more complicated parameters, i.e. K_s. This study was aimed at developing a local best-fit of data models which are quite needed in numerous agricultural and modeling applications for the Egyptian soils. These local models will perfectly predict K_s based on effective porosity ( BF1), since this model exhibits a degree of universality, or on particle size distribution, organic matter, and bulk density (BF2) for three major Egyptian soils: alluvial-lacustrine, calcareous, and sandy. Additionally, testing the reliability of predicting K_s of these soils using the proposed models: Ahuja et al., 1989 (AHJ), Campbell and Campbell, 1982 (C&C), Campbell, 1985 (CAM), Marie a, 1987 (MRA), Marie b, 1987 (MRB),  Rawls and Brakensiek, 1989 (R&B), and  Saxton et al., 1986 (SAX). Data showed that the predictive models resulted in relative magnitude of reliability based on the highest possible mean and mean relative errors and their standard deviations (high percentage indicates less reliable) as 70.8, 9.1, 9.0, 10.8, 9.0, 63.2, 59.2, 30.1, and 10.4٪  for alluvial-lacustrine soil; 99.6, 8.6, 6.8, 12.1, 10.7, 60.9, 10.5, 20.2, and 11.1٪  for calcareous soil; 67.1, 57.5, 66.4, 55.7, 57.8, 60.0, 60.9, 60.6, and 75.3٪ for sandy soil; and 51.5, 50.9, 31.8, 42.3, 36.2, 98.4, 83.3, 43.6, and 25.9٪  for all over studied soils with the AHJ, BF1, BF2, C&C, CAM, MRA, MRB, R&B, and SAX models, respectively. The locally developed BF1 and BF2 models provide reasonable and reliable prediction of  K_s based on the available input data. Generally, if a local model is not available, the CAM, MRB, C&C, and SAX models will provide best estimates of K_s in  alluvial-lacustrine,  calcareous, sandy, and all over studied soils, respectively. With more limited input data, the CAM model best described K_s for the given soils.