This paper studies prediction of future failure (rates) by hierarchical empirical Bayes (EB) Poisson regression methodologies. Both a gamma distributed super-population as well as a more robust (long-tailed) log student- t super-population are considered. Simulation results are reported concerning predicted Poisson rates. The results tentatively suggest that a hierarchical model with gamma super-population can effectively adapt to data coming from a log-Student-t-super-population particularly if the additional computation involved with estimation for the log-Student-t hierarchical model is burdensome.