The aim of this paper is to study the interactions between categorization and decision making. While these two fields have mostly evolved separately, we introduce a model for categorization processes that is derived from a general decision-making heuristics. Such a model is able to account for both tasks involved in categorization, i.e. classification and category construction. One of the most important principle that support this work is the bounded rationality as introduced by Simon [Simon, 1955] in order to take into account the human limitations. We designed a connectionist network, called Categ ART, to implement our categorization model. We illustrate our method for an experiment where subjects had to categorize saving schemes. Categ ART produces automatically polynomials that can be interpreted as classification rules based on prototypes. The analysis of these rules allows us to suggest two anchoring and adjustment heuristics that seem to play an important role in our experiment.