<p>This study aims to determine the optimum extraction conditions that maximize the biological activities of <i>Agaricus campestris</i> and <i>Agaricus bisporus</i> species. In the study, a total of 64 extraction experiments were carried out at different temperatures, time and solvent concentrations and the obtained data were modeled with Artificial Neural Network (ANN) and optimized with Genetic Algorithm (GA). After determining the optimum extraction parameters, antioxidant, anticholinesterase and antiproliferative activities and phenolic contents of the produced extracts were analyzed. As a result of single and multi-objective optimization studies of <i>A. campestris</i> and <i>A. bisporus</i>, extract concentration was determined. In antioxidant analyses, it was observed that <i>A. campestris</i> extracts had higher total antioxidant capacity (TAS) and lower total oxidant level (TOS) compared to <i>A. bisporus</i> extracts. Anticholinesterase activity tests revealed that <i>A. campestris </i>extracts showed stronger inhibitory effect compared to <i>A. bisporus</i>. In addition, in the antiproliferative activity analyses performed on the A549 lung cancer cell line, it was determined that the extracts produced with ANN-GA optimization suppressed cell proliferation. Phenolic compound analyses showed that antioxidant compounds such as gallic acid, protocatechuic acid and caffeic acid were found at high levels in <i>A. campestris</i> extracts. The results show that ANN-GA supported optimization processes enrich the bioactive components of mushroom extracts and that these methods may be effective in biotechnological applications.</p>