The Rescorla-Wagner model has been the most influential theory of associative learning to emerge from the study of animal behavior over the last 25 years. Recently, equivalence to this model has become a benchmark in assessing connectionist models, with such equivalence often achieved by incorporating the Widrow-Hoff delta rule. This article presents the Rescorla-Wagner model's basic assumptions, reviews some of the model's predictive successes and failures, relates the failures to the model's assumptions, and discusses the model's heuristic value. It is concluded that the model has had a positive influence on the study of simple associative learning by stimulating research and contributing to new model development. However, this benefit should neither lead to the model being regarded as inherently "correct" nor imply that its predictions can be profitably used to assess other models.