<p>Adsorption is a pivotal process in environmental cleanup and wastewater treatment due to its simplicity, cost-effectiveness, and sustainability. The quantification of adsorption is often expressed through Adsorption Isotherms, which model the substance adsorbed by a substrate at equilibrium. Understanding single, multi-component, and competitive adsorption isotherms is crucial for designing effective water treatment systems. Experimental data modeling plays a significant role in predicting adsorption mechanisms. This review explores isotherm models'foundational knowledge and practical applications, offering insights into their conceptual framework and utility. It covers single and multi-component contexts, extensively discussing various isotherm models and their parameters. The debate over linearization in adsorption equations is addressed, highlighting factors influencing parameter determination such as linearization method, experimental error, and data range. The paper elucidates techniques like linear and nonlinear regression analysis and error functions for optimal adsorption data analysis, providing a comprehensive understanding of the subject.</p> Graphical Abstract <p></p>