For the reliability demonstration of a repairable system, testers expediently assume that the rate of occurrence of failures (ROCOF) can be modeled by a homogenous Poisson process (HPP), also called an ordinary renewal process (ORP), and therefore the times between failure, or interarrival times, are exponentially distributed with a constant mean time between failures (MTBF). This often-used test is colloquially called the “classical MTBF test” because it has been widely used by both government and industry for the past 50 years. The test is simple; operate a system for a period and the sample estimate for MTBF is the operating time divided by the number of failures. A confidence interval is applied to the sample estimate to determine the test result. This paper considers the validity of the test result if the repairable system has an increasing or decreasing MTBF, that is, a nonhomogeneous Poisson process (NHPP). Specifically, the change in consumer’s risk is analyzed if the repairable system has a decreasing MTBF (increasing ROCOF). A simple risk mitigation strategy consisting of a burn-in period equal to the threshold MTBF is also considered and found to be effective. The classical MTBF test is shown to be a robust test and a burn-in period prior to testing makes the classical MTBF test even more robust.