This paper defines a framework for artificial reasoning called Subjective Logic, which consists of a belief model called opinion and set of operations for combining opinions. Subjective Logic is an extension of standard logic that uses continuous uncertainty and belief parameters instead of only discrete truth values. It can also be seen as an extension of classical probability calculus by using a second order probability representation instead of the standard first order representation. In addition to the standard logical operations, Subjective Logic contains some operations specific for belief theory such as consensus and recommendation. In particular, we show that Dempster’s consensus rule is inconsistent with Bayes’ rule and therefore is wrong, and provide an alternative rule with a solid mathematical basis. Subjective Logic is directly compatible with traditional mathematical frameworks, but is also suitable for handling ignorance and uncertainty which is required in artificial intelligence.