This study explores the effect of ultra-sonication on the extraction of phenolic compounds of cashew apple bagasse (CAB). The extraction was conducted at different combinations of treatment time (5-15 min), ultrasound amplitude (30-60%), and bagasse to solvent ratio (30-50 g/ml) for maximum yield of total phenolic content (TPC), total tannin content (TTC), and β-carotene content. Both response surface methodology (RSM) and artificial neural network (ANN) were used to model and optimize the process parameters. The optimum conditions achieved using RSM were: treatment time of 12 min, ultrasound amplitude of 55%, and bagasse to solvent ratio of 45 g/ml. In contrast, the optimum conditions proposed by ANN were: treatment time of 15 min, 60% amplitude, and 50 g/ml bagasse to solvent ratio. The TPC, TTC, and β-carotene content was determined under RSM optimized conditions as 29.04 mg GAE/g, 26.70 μg tannic acid/g, and 18.12 μg/g, respectively and under ANN optimized conditions as 30.61 mg GAE/g, 30.80 μg tannic acid/g, and 19.50 μg/ g, respectively. All the statistical parameters showed the lowest value in the ANN model than the RSM model with the highest coefficient of determination (R 2 ). The measured value of the TPC, TTC, and β-carotene content at optimized conditions were in agreement with the predicted value obtained from the above models. Besides these, the ultra-sonication significantly increased the TPC, TTC, and β-carotene content while comparing with conventional solvent extraction. Hence, this method could be an effective green method over conventional technologies to extract phenolic compounds from CAB.