ADHD, a neurodevelopmental disorder characterized by hyperactivity, inattention, and impulsivity, has many detrimental impacts and is out of proportion to age. ADHD causes executive failure and emotional instability, which can lower academic performance. We propose a machine learning and artificial intelligence-driven approach to diagnose and early detect this disease and assist ADHD medicine. SVM, logistic regression, XGBoost, AdaBoost, and two deep learning models were applied to our dataset (ANN and CNN). Our ANN model had 99% accuracy in dependability, expandability, and generalizability. We plan to use our machine learning technology to enhance ADHD diagnosis and treatment for everyone.