Artificial Intelligence (AI) has revolutionized various fields by enabling machines to perform tasks that typically require human intelligence. Central to AI are decision models, which utilize algorithms to analyze data and make predictions or decisions based on that information. These models can range from simple linear regressions to complex neural networks, each with its own strengths and weaknesses. Understanding how these models work, including their mathematical foundations and practical implementations, is crucial for developing effective AI systems. As AI continues to evolve, exploring innovative approaches and optimizing performance remains a key focus for researchers and practitioners alike.