<p>Corrosion of concrete structures has been one of the major causes of structural failure. The corrosion process can be tracked using several electrochemical techniques. But most of these methods pertain to visual inspection and remedial measures are resorted to only when severe damage has occurred. This makes the entire process much more complicated and uneconomical. Thus, early detection of deterioration and timely remedial action on the affected area would ensure optimal utilization of the structure and longevity. With the advantages of non-invasion, non-radiation, low-cost, and high-speed, electrical resistivity measurement is a promising technique in this regard. This paper proposes a model to quantify the corrosion rate using electrical resistivity as a parameter. The impressed current method was employed to initiate the chloride-induced corrosion process. The experimental variables considered include the grade of concrete, duration of corrosion, reinforcement cover, reinforcement diameter, and their corresponding electrical resistivity values. The experimental data is defuzzied using the adaptive neuro fuzzy inference system approach in MATLAB. A stepwise linear mathematical model is then developed, integrating both linear and quadratic terms to capture the intricate nature of corrosion phenomena. The proposed model demonstrates a significant coefficient of determination (R²) value of 0.87, indicating its efficacy in predicting corrosion rates.</p>