This book presents a novel fusion of environmental science, materials engineering, and intelligent modeling tools in order to provide a thorough investigation of advanced wastewater treatment employing chitosan derivatives. It focuses on employing chemically modified chitosan, a sustainable and biodegradable bio-adsorbent, to adsorb contaminants, including colors and heavy metals, from both manufactured and natural wastewater. This book's distinctive strength is the way it combines three potent predictive tools: the adaptive neuro-fuzzy inference system (ANFIS), which combines the advantages of fuzzy logic and neural networks, response surface methodology (RSM) for statistical optimization, and artificial neural networks (ANNs) for capturing intricate nonlinear relationships. Case examples, model comparisons, performance data, and software applications utilizing programs like MATLAB, R, and Design-Expert are used to properly demonstrate each technique. With step-by-step instructions, experimental data, and useful insights, this book, which is intended for both scholars and practitioners, links theory and practice. By relating wastewater treatment techniques to green chemistry and the circular economy, it also highlights sustainability. This book gives you the information and resources you need to predict, optimize, and implement environmentally sustainable wastewater solutions using cutting-edge computational techniques, regardless of your background-student, academic, or professional.