A machine learning method has been developed to detect Majorana zero modes (MZMs) from experimental data, achieving significant accuracy. This approach utilizes quantum transport simulations and topological data analysis, providing a simpler and more effective method to identify these quantum states, crucial for the advancement of fault-tolerant quantum computing. This work demonstrates a significant step toward practical, fault-tolerant quantum systems, making complex quantum behaviors accessible and understandable for nonspecialists.