Decision situations with incomplete information are characterized by a decision maker without a precisely defined, stable preference structure; by probability distributions not known completely; or by an inexact evaluation of consequences. Within the paper a general framework for decision making with incomplete information is presented which shows how to solve problems from descriptive as well as prescriptive decision theory. Based on this framework an overview of existing methods which are particularly suitable for handling incomplete information is given.