Electrochemical characterization techniques have become indispensable for understanding corrosion phenomena, enabling both fundamental mechanistic insights and practical corrosion monitoring across diverse industrial applications. This comprehensive review systematically examines the principles, applications, and data interpretation strategies for key electrochemical methods used in corrosion research. Cyclic voltammetry (CV) has emerged as a powerful mechanistic probe, capturing real-time redox activity and surface transformations, though historically underutilized due to the irreversible nature of corrosion reactions . Electrochemical impedance spectroscopy (EIS) remains the most versatile technique, providing frequency-dependent information on charge transfer resistance, double-layer capacitance, and diffusion processes, with applications ranging from reinforced concrete diagnosis to nanostructured coating evaluation . Potentiodynamic polarization enables rapid determination of corrosion current density, Tafel slopes, and pitting potentials through the Stern–Geary relationship . Electrochemical noise analysis detects spontaneous current and potential fluctuations sensitive to localized corrosion events such as metastable pit growth . Recent advances in machine learning have revolutionized data interpretation, with hybrid models achieving R² > 0.99 prediction accuracy for corrosion rate forecasting through integration of swarm intelligence optimization with deep learning architectures . Four-dimensional impedance analysis has emerged for time-varying systems, enabling instantaneous impedance determination during non-stationary corrosion processes . This review concludes that effective corrosion characterization requires integrated approaches combining complementary techniques with advanced data analytics, bridging laboratory mechanistic understanding with field-applicable monitoring solutions.