Machine Learning Approaches to Concrete Strength Prediction combines traditional engineering with modern data science reshaping how we predict concrete strength. Focusing on concrete mixes that use sand manufactured sand (M-sand) and laterite soil as fine aggregates this book provides a practical guide to machine learning techniques like Linear Regression Decision Trees Random Forest Support Vector Regression and Gradient Boosting. With clear explanations and a real-world case study it equips readers with the knowledge to apply data-driven approaches in construction.