This analysis explores the "Real Estate" dataset from Kaggle using linear regression in R. After cleaning and transforming the data, several predictive models are built based on proximity to public transport, convenience stores, and geographic coordinates. The final model demonstrates how key location-based features influence price per square meter. Visualizations and statistical metrics are used throughout to evaluate model performance and interpret results.