We need specific and competent adsorbents to remove arsenic and bring it down to permissible levels in drinking water. Therefore, industrial byproducts are extensively applied to produce large amounts of natural adsorbents. Similarly, managing optimum arsenic adsorption with palm oil clinker sand (POCS) is possible through a careful statistical planning of adsorption variables. We plan and perform a minimum number of experiments to (1) obtain optimum arsenic adsorption and (2) provide a new possible application opportunity to the industrial waste managers and future planners. We observed that adsorption of arsenic was dependent on the pH of the system, initial concentration of arsenic (mg L−1), amount (mg) of POCS, and temperature of the bio-adsorption system. A correlation among the study variables was constructed by three-dimensional (3D) response surfaces and two-dimensional (2D) contour plots based on central composite design (CCD) experiments in a batch mode of study. A quadratic model fitted well with the experimental data and better explained the superiority of current bio-adsorption system and efficient removal of arsenic from water samples. We confirmed that the selected variables were experimentally and statistically significant and controlled the overall adsorption response by the batch system. A comparative and thorough analysis of the adsorption process confirmed that selected variables were mutually interacting in a nonlinear fashion in this study. Excellent experimental results and external comparative studies prove the relative importance of the present model and adsorption system for arsenic remediation biotechnology.