Background: Opuntia ficus-indica (OFI) cladodes are valuable and underestimated by-products that provide significant amounts of biologically active compounds. In this paper, microwave-assisted extraction (MAE) was performed for the recovery of phenolic compounds from OFI cladodes using two approaches: response surface methodology (RSM) and artificial neural network–genetic algorithm (ANN-GA), which were then compared following statistical indicators. Materials and Methods: Four independent factors were employed in the optimization process (solvent concentration, microwave power, irradiation time, and solid-to-liquid ratio) by selecting the total phenolic content (TPC), estimated by the Folin–Ciocalteu method, as a response. The optimized extract was tested for antioxidant capacity using the Folin–Ciocalteu reagent, Trolox Equivalent Antioxidant Capacity (TEAC), and oxygen radical absorbance capacity (ORAC) assays and for antimicrobial activity against 16 pathogenic strains using the agar well diffusion method. Results: The maximum TPC values predicted with maximizing desirability function for RSM were 2177.01 mg GAE/100 g DW and 1827.38 mg GAE/100 g DW for the ANN. Both models presented certain advantages and could be considered reliable tools for predictability and accuracy purposes. Using these conditions, the extract presented high antioxidant capacity for FCR assay (13.43 ± 0.62 mg GAE/g DW), TEAC (10.18 ± 0.47 µmol TE/g DW), and ORAC (205.47 ± 19.23 µmol TE/g DW). The antimicrobial activity of the optimized extract was pronounced only with respect to S. aureus alimentarius, Streptococcus, E. coli, P. aeruginosa, and A. flavus. Conclusions: This study underlines the high effectiveness of the optimization approaches in providing a maximum recovery of bioactive compounds from OFI cladodes to formulate food and pharmaceutical products with functional qualities.