The shaft resistance of rock-socketed piles (RSPs) is primarily influenced by the interactions between the pile, rock and any soft interface materials. This study presents a fundamental experimental and numerical investigation to predict the shaft resistance of model RSPs in soft rocks through a comprehensive shear strength framework incorporating the major variables such as roughness and smear fabric. By calibrating the Discrete Element Method (DEM) results with the experimental outcomes, this study evaluates the load-resistance attributes of RSPs in three different soft rocks for a wide range of roughness and smear configurations. The interface roughness effect of the RSPs in terms of the friction coefficient was correlated with the ultimate shaft resistances, uniaxial compressive strength and Young’s modulus of the rock. The study then incorporated the effect of smear fabric (placement, thickness and area proportion) in the shear strength framework of clean shafts. Comprehensive review of the DEM results revealed that the socket roughness effect diminishes at a critical roughness factor (RF)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$({\ ext{RF}})$$\\end{document} of 0.4, beyond which the smear predominantly influences the shaft capacity. Following this, the effects of roughness and smear fabric were incorporated into a single equation representing the interface shear strength of RSPs, where the existence of smear results in a maximum reduction of up to 75% of the ultimate shaft resistance. The distinctive feature of this unified interface shear strength framework lies in its integration of the new smear fabric parameter and the linkage to the mechanical properties of soft rocks, which is the limitation of the earlier studies. It thereby sets a strong base for future studies aimed at advancing the pile-rock interface models.