The Geometry of Change is a field guide to building models that are both honest about complexity and useful in practice. It connects three pillars—how systems work (mechanisms), how we encode them (models), and how we learn from the world (measurement)—into a coherent workflow for decision-making. Beginning with why we model at all, it explores growth patterns and limits, stochasticity and structure, interactions and spread, spatial and metapopulation thinking, and the challenges of fitting parameters from real data. It then turns to interpreting signals—trends, cycles, and regimes—showing how to separate what persists from what repeats and what truly changes the rules. Throughout, it emphasizes calibration, uncertainty, fairness, and governance, translating technical craft into operational playbooks and ethics-aware practices. The result is a practical, human-centered approach to turning data into insight, and insight into action, across ecological, urban, digital, and organizational systems.