It is important to predict and analyze user acceptance of computer technology in order to address success and failures of technological products. The Theory of Reasoned Action has been used for two decades in empirical studies to predict user acceptance of computer technology based on parameters of attitude, subjective norm and behavioral intention. Empirical studies are expensive to carry out and inflexible in predicting the diffusion of parameters over time. In this paper we introduce an agent-based implementation that implements a simple version of the theory of reasoned action model. Our agent-based implementation simulates continuous data compared to empirical studies, which collect static data over discrete intervals of time. Empirical studies are unable to account for the changes in data between successive time intervals. Our implementation is cost effective and easy to use. The results we produced corroborate the results obtained from the last few decades of empirical research in this field.