This paper is concerned with a Bayes prediction problem in the exponential distribution under random censorship. Using censored
samples, we work out a prediction interval for a sum of interest which consists of some future samples. Differing from the
general Bayes approach, we do not specify the prior distribution of the parameter, and only a first moment condition on the
prior is assumed. ... [Show full abstract] Simulation studies are conducted to exhibit the coverage probabilities of the prediction interval.