machine learning is leveraged to dynamically optimize obfuscation patterns and predict the most effective techniques tailored to specific software environments, which marks a considerable improvement over traditional methods that often require manual intervention and are prone to errors. The design and implementation of an intelligent system for obfuscating .NET programming languages using artificial intelligence. The proposed system leverages deep learning techniques to enhance code security and complexity. The system's architecture includes components such as a preprocessing module, AI-based obfuscation module, quality verification module, data storage system, and reporting module. Detailed implementation strategies using .NET tools.