In this paper a method of computer-aided optimization of 3-D conformal treatment plans is presented which incorporates models to predict the clinical consequences of resulting dose distributions. Even though these models are simplistic, it is submitted that their intelligent use leads to treatment plans which indicate lower normal tissue complications and higher tumor control. Dose distribution data, biological models, and observed normal tissue and tumor response data are used to compute tumor control and normal tissue complication probabilities for each of the critical normal structures encountered in a treatment plan. These quantities are combined into a single score using an objective function which incorporates the importance of each end point as assessed by the physician. Using the "simulated annealing" method of optimization, the beam weights are adjusted to maximize the score. Additional constraints are applied to ensure consistency of the results of optimization with the judgment of the physician. These optimization methods have been applied to conformal treatment plans consisting of multiple fixed fields with conformal field shaping. The results indicate that the methods presented have considerable potential.