Discusses the application of artificial intelligence (AI) techniques in machining processes, focusing on Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and metaheuristic algorithms for prediction and optimization. ANNs, modeled after the human nervous system, are used to predict surface roughness, optimize machining parameters, and monitor tool wear by learning complex, nonlinear relationships in data. ANFIS combines fuzzy logic with neural networks to handle complex parameter relationships, providing a more effective analysis and optimization tool. Metaheuristic algorithms, such as Genetic Algorithms (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO), are used to enhance ANFIS performance in predicting machining outcomes like tool vibration and surface roughness. Studies demonstrate that combining these AI techniques significantly improves accuracy and optimization in machining processes, outperforming traditional methods.