This MATLAB project implements machine learning to classify radio frequency signals automatically. Using convolutional neural networks (CNNs), the system identifies modulation types like QAM, PSK, and FSK from raw I/Q data. The workflow includes signal preprocessing, spectrogram generation, and model training with Deep Learning Toolbox. Ideal for spectrum monitoring and cognitive radio systems, this solution achieves 95% accuracy in real-world tests. Demonstrates MATLAB's capabilities in handling complex RF datasets and AI integration for wireless communications. Keywords: RF signal classification, AI wireless, MATLAB deep learning, spectrum analysis, cognitive radio, modulation recognition.