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The Choice Of A Suitable Hairstyle Plays A Significant Role In Enhancing Personal Appearance And Confidence. However, Selecting The Most Appropriate Hairstyle Often Depends On Factors Such As Face Shape, Facial Features, And Individual Preferences, Making It A Challenging And Subjective Process. Traditional Methods Of Hairstyle Selection Rely On Manual Consultation With Experts, Which Can Be Time-consuming, Inconsistent, And Costly. To Address This Challenge, This Study Presents The Design And Implementation Of A Hair Recommendation System Based On Face Recognition. The System Employs Computer Vision Techniques For Face Detection And Feature Extraction, Classifying Face Shapes Such As Oval, Round, Square, And Heart-shaped. Using These Classifications, A Recommendation Engine Suggests Suitable Hairstyles Tailored To The User’s Facial Attributes. The Proposed Framework Integrates Image Preprocessing, Facial Landmark Detection, Feature Analysis, And Machine Learning Models To Provide Personalized Hairstyle Suggestions In Real Time. Experimental Results Demonstrate That The System Offers Accurate Face Shape Classification And Effective Hairstyle Recommendations, Thereby Enhancing User Satisfaction. This Approach Highlights The Potential Of Artificial Intelligence And Face Recognition Technologies In Personal Grooming, Fashion, And Virtual Try-on Applications.