<p>Developing an affordable, stable, and efficient photocatalyst is essential for addressing environmental pollution. In this study, A Sulfur-doped Zinc oxide(S@ZnO) and sulfur-doped Zinc oxide/Chitosan (S@ZnO/Chitosan) composites with enhanced photocatalytic capabilities for degrading tetracycline under visible light was synthesized. The synthesized composites were characterized using techniques such as X-ray diffraction (XRD), Field-Emission Scanning Electron Microscopy (FESEM), and energy-dispersive X-ray spectroscopy (EDX) to confirm their structure and composition. The photocatalytic activity was assessed by measuring tetracycline degradation under visible. Machine learning (Random Forest regression) is employed to model and predict degradation efficiency. It evaluated by a 10 fold cross-validation, and the results clearly show that an average R² of 0.978 and a relatively low average MSE of 15.334 across the 10 folds, indicating strong predictive performance and accuracy. Importance of individual features (TC concentration, pH, dosage, and time) and their products are evaluated using Random Forest Average Feature Importance (Gini) and SHAP(SHapley Additive exPlanations) Global Feature. Our findings reveal that the S@ZnO/Chitosan nanocomposite achieved a 95% degradation rate of tetracycline in 120&#xa0;min, compared to 50% degradation using S@ZnO alone. Kinetic modeling confirmed pseudo-first-order behavior, with rate constant for the chitosan composite was 0.016&#xa0;min⁻¹, significantly higher than 0.005&#xa0;min⁻¹ for S@ZnO. These results demonstrate that incorporating chitosan into S@ZnO. substantially enhances photocatalytic efficiency by improving electron-hole pair separation and increasing the lifetime of photogenerated charges. This innovative S@ZnO. /chitosan nanocomposite shows significant potential for practical applications in environmental remediation.</p>