A broad range of well-structured problems--embracing forms of diagnosis, catalog selection, and skeletal planning--are solved in expert computer systems by the method of heuristic classification. These programs have a characteristic inference structure that systematically relates data to a pre-enumerated set of solutions by abstraction, heuristic association, and refinement. In contrast to previous descriptions of classification reasoning, particularly in psychology, this analysis emphasizes the role of a heuristic in routine problem solving as a non-hierarchical, direct association between concepts. In contrast with other descriptions of expert systems, this analysis specifies the knowledge needed to solve a problem, independent of its representation in a particular computer language. The heuristic classification problem-solving model provides a useful framework for characterizing kinds of problems, for designing representation tools, and for understanding non-classification (constructive) problem-solving methods. This 12-part report includes the following sections: (1) Introduction; (2) The Heuristic Classification Method Defined; (3) Examples of Heuristic Classification; (4) Understanding Heuristic Classification; (5) Analysis of Problem Types in Terms of Systems; (6) Inference Strategies for Heuristic Classification; (7) Constructive Problem Solving, An Introduction; (8) Relating Tools, Methods, and Tasks; (9) Knowledge-Level Analysis; (10) Related Analyses in Psychology and Artificial Intelligence; (11) Summary of Key Observations; and (12) Implications. Six pages of references complete the document. (Author/THC)