What are the goals of mathematical modeling in biology? What is the proper philosophy, and what is the best methodology, for my particular problem and data set? At the present time there is very little agreement about either philosophy or technique in this area. This book provides an original perspective on these perplexing problems. Included are a new method for fitting deterministic models with active noise (appearing here for the first time), and an old method adapted for use in otherwise intractable cases. The reader will learn about the history of modeling and the many controversies and disputes it has engendered over the last 80 years. Also included are examples of the methodology applied to historical data sets and simulations from ``chaotic" models.