Statistical optimization of the biodegradation of two keratinous wastes directed by Bacillus subtilis recombinant cells was carried out by means of a response surface methodology. A Box-Behnken design was employed to predict the optimal levels of three variables namely, keratin percent, incubation time and inoculum size. Analysis of variance revealed that, only keratin percent had the highest significant effect. Canonical analysis and ridge max analysis were used to get the optimal levels of the three predictors along with the optimum levels of the responses. The optimal sets of predicted and validated levels of the three variables were [7.69% (w/v) feathers, 96.58 h and 1.28% (v/v) inoculum size] and [8% (w/v) feathers, 98.45 h, 3.9% (v/v) inoculum size] to achieve the highest levels of soluble proteins (1.25-1.7 mg/ml) and NH(2)-free amino groups (245.82-270.0 μmol leucine/ml), respectively upon using three optimized feathers-based media. These values represented 83.67-100% and 100% adequacy for the models of soluble proteins and NH(2)-free amino groups, respectively. While, [8.23% (w/v) sheep wool, 5.52% (v/v) inoculum size and 46.58 h] and [8.33% (w/v) sheep wool, 5.89% (v/v) inoculum size and 63.46 h] were the optimal sets of predicted and validated levels of the above variables to achieve the highest yields of soluble proteins (3.4-4.6 mg/ml) and NH(2)-free amino groups (290.9-302.0 μmol leucine/ml), respectively upon using three optimized sheep wool-based media. These values represented 100% adequacy for the models of soluble proteins and NH(2)-free amino groups. By the end of the optimization strategy, a fold enhancement (2.14-2.43 and 1.78-2.12) in the levels of released soluble proteins and NH(2)-free amino groups, respectively was obtained upon using three optimized feathers-based media. However, a fold enhancement (4.25-5.75 and 2.42-2.5) in the levels of soluble proteins and NH(2)-free amino groups, respectively was obtained upon using three optimized sheep wool-based media. Data would encourage pilot scale optimization of the biodegradation of these wastes.