<p>Characterizing pore size distribution (PSD) in carbonate reservoirs remains a significant challenge due to their complex and heterogeneous pore structures. This study introduces a novel integration of spectral induced polarization (SIP) with advanced image analysis and conventional petrophysical techniques to non-destructively quantify PSD and infer flow-related properties. A key innovation lies in the application of a modified open-source MATLAB algorithm to invert SIP spectra and extract relaxation time distributions, which were then modeled using a Double Cole–Cole function. The SIP-derived PSDs showed strong agreement with mercury intrusion porosimetry (MIP) data, validating the approach. Furthermore, high-resolution scanning electron microscopy (SEM) images were processed using a watershed-based segmentation technique to resolve microporosity and complement SIP estimates. While both MIP and SEM are destructive methods, they were used solely as benchmarking tools to constrain and validate SIP interpretations. A quantitative relationship between SIP quadrature conductivity and critical petrophysical parameters such as grain size variation and permeability were evaluated using existing theoretical models. The study demonstrates the potential of SIP as a standalone predictive tool for reservoir quality assessment, reducing reliance on destructive laboratory methods. These findings contribute new insights into the electro facies behavior of carbonates and offer a scalable approach for subsurface characterization in complex reservoir settings.</p>