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Soon after the birth of the flourishing research area of model checking in the early eighties, researchers started to apply this technique to finite automata equipped with probabilities. The initial focus was on qualitative properties - e.g., does a program terminate with probability one? - but later efficient algorithms were developed for quantitative questions as well. Model checking of probabilistic models received quite some attention in the late nineties, and this popularity lasts until today. Application areas are, among others, security, distributed algorithms, systems biology, and performance analysis. What is the current state of this field? Probabilistic verification, quo vadis? This paper surveys the main achievements during the last two decades, reports on recent advances, and attempts to point out some research challenges for the coming years.