Model-based data extraction is the best approach when dealing with documents where data points don't have a fixed structure or position. This method leverages machine learning models to understand and extract data based on patterns and contexts, rather than relying on predefined rules or manual inputs. This makes it more adaptable and efficient for handling variations in document layouts.