Empirical modeling involves creating models based on observed data rather than theoretical assumptions, allowing for predictions and insights that are grounded in real-world evidence. This approach is particularly useful in complex systems where theoretical models are difficult to establish or validate, and it often employs statistical techniques to identify patterns and relationships within the data.