RANSAC (Random Sample Consensus) has been a cornerstone of robust estimation in computer vision since its introduction in 1981. It remains highly relevant in 2025, as many vision applications still rely on detecting and handling outliers in data. This tutorial, “RANSAC in 2025”, aims to provide a comprehensive update on the latest advancements of RANSAC and its family of algorithms. We will balance theoretical foundations (to understand how and why RANSAC works) with practical applications (to demonstrate its use in real-world vision problems). By covering both classic principles and cutting-edge improvements, the tutorial will equip researchers and practitioners with state-of-the-art techniques for robust model fitting in computer vision.