“demonic” nondeterminism, representing abstraction from (or ignorance of) which of two program fragments will be executed. By introducing probabilistic nondeterminism into GCL, we provide a means with which also probabilistic programs can be rigorously developed and reasoned about. The programming logic of “weakest preconditions” for GCL becomes a logic of “greatest pre-expectations” for what we call pGCL. An expectation is a generalized predicate suitable for expressing quantitative properties such as “the probability of achieving a postcondition”. pGCL is suitable for describing random algorithms, at least over discrete distributions. In our presentation of it and its logic we give a number of small examples, and two case studies. The first illustrates probabilistic “almost-certain” termination; the second case study illustrates approximated probabilities, abstraction and refinement. After a brief historical account of work on probabilistic semantics in Section ...