4-chlorophenol (4-CP) is a hazardous contaminant that is hardly removed by some technologies. This study investigated the biodegradation, and physical 4-CP removal by a mixed microbial consortium in the Airlift packed bed bioreactor (ALPBB) and modeling by an artificial neural network (ANN) for first the time. The removal efficiency of ALPBB was investigated at 4-CP(1-1000 mg/L) and hydraulic retention time (HRT)(6-96 hr) by HPLC. The results showed that removal efficiency decreased from 85 at 1 to 0.03% at 1000 mg/L, with increasing 4-CP concentration and HRT decreasing. BOD5/COD increased with increasing exposure time and concentration decreasing, from 0.05 at 1000 to 0.96 at 1 mg/L. With time increasing, the correlation between COD and 4-CP removal increased (R2 = 0.5, HRT = 96 h). There was a positive correlation between the removal of 4-CP and SCOD by curve fitting was R2 = 0.93 and 0.96, respectively. Moreover, the kinetics of 4-CP removal follows the first-order and pseudo-first-order equation at 1 mg/L and other concentrations, respectively. 4-CP removal modeling has shown that the 2:3:1 and 2:4:1 were the best structures (MSE: physical = 0.126 and biological = 0.9)(R2allphysical = 0.999 and R2testphysical = 0.999) and (R2allbiological = 0.71, and R2testbiological = 0.997) for 4-CP removal. Also, the output obtained by the ANN prediction of 4-CP was correlated to the actual data (R2physical = 0.9997 and R2biological = 0.59). Based on the results, ALPBB with up-flow submerged aeration is a suitable option for the lower concentration of 4-CP, but it had less efficiency at high concentrations. So, physical removal of 4-CP was predominant in biological treatment. Therefore, the modification of this reactor for 4-CP removal is suggested at high concentrations.