Rice polish, a waste from the rice milling industry, was utilized as a potential biosorbent for removal of arsenic from aqueous solution. Optimization of process variables (pH, initial metal concentration, and temperature) and their cumulative effect were investigated using Box-Behnken Design (BBD) with only 15 sets of experimental runs. A second-order polynomial regression model was used, and results predicted showed high value of regression coefficients (R-2, i.e., 95.69% for As(III) and 98.42% for As(V)) indicating good agreement with experimental data. The main effect plot showed uptake of arsenic having a curved relationship with pH, initial metal ion concentration having a positive effect, and temperature having a negative effect. The maximum removal of As(III) (41.18 mu g/g) and As(V) (49 mu g/g) predicted by contour and optimization plot was achieved at pH 6.84 and 4.29, respectively, at an initial metal ion concentration of 1000 mu g/L, temperature 20 degrees C, and biomass dose of 1 g/50 mL. Scanning electron microscopy (SEM) analysis was carried out to find out the changes on the biosorbent surface during the sorption process.