In this study, a statistical Design of Experiments (DOE) method combined with response surface methodology (RSM) was used for identification and optimization of factors influencing the extraction of aluminium from coal fly ash (CFA). The factors investigated included: acid concentration, leaching time, temperature and solid to liquid ratio. The significance of each factor and associated interactive effects were evaluated using a two-level factorial statistical design (24) in conjunction with statistical software based on quadratic programming. Results showed temperature and time to be statistically significant; other factors and interactive effects were found to be insignificant. Optimization of the two significant factors was achieved by employing the second order quadratic regression model in combination with the central composite rotatable design (CCRD). From the prediction model, an optimal aluminium extraction efficiency of 23.95% was obtained at optimal values of 82 C temperature and 10.2 h leaching time. A confirmatory test showed an aluminium extraction efficiency of 24.8%, giving an error margin of 3.4%, with a linear correlation coefficient of 97.8%, hence verifying the fitness of the model and experimental data. The 24.8% extraction efficiency represents 89.3% aluminium extraction from the amorphous phase of CFA. (C) 2013 Elsevier B.V. All rights reserved.