Formal models in biology are traditionally of two types: simulation models in which individual components are described in detail with extensive empirical support for parameters, and phenomenological models, in which collective behaviour is described in the hope of identifying critical variables and parameters. The advantage of simulation is greater realism but at a cost of limited tractability, whereas the advantage of phenomenological models, is greater tractability and insight but at a cost of reduced predictive power. Simulation models and phenomenological models lie on a continuum, with phenomenological models being a limiting case of simulation models. I survey these two levels of model description in genetics, molecular biology, immunology and ecology. I suggest that evolutionary considerations of the levels of selection provides an important justification for many phenomenological models. In effect, evolution reduces the dimension of biological systems by promoting common paths towards increased fitness.