An envelope plot is a modification of the familiar probability plot that compares a set of data to a probability distribution. Simulation is used to assess and display the variability inherent in a probability plot. The resulting plot has been used as an informal check of the hypothesis that the data were sampled from the distribution. This paper examines the properties of the envelope plot as a formal goodness-of-fit test. Advantages include its versatility and graphical nature. However, it is shown that commonly used numbers of simulations lead to rather high Type I error rates; when the significance level is controlled, the power of the test may be low.