This paper studies quantitative model checking of infinite tree-like (continuous-time) Markov chains. These treestructured quasi-birth death processes are equivalent to probabilistic pushdown automata and recursive Markov chains and are widely used in the field of performance evaluation. We determine time-bounded reachability probabilities in these processeswhich with direct methods, i.e., uniformization, results in an exponential blow-up-by applying abstraction. We contrast abstraction based on Markov decision processes (MDPs) and interval-based abstraction; study various schemes to partition the state space, and empirically show their influence on the accuracy of the obtained reachability probabilities. Results show that gridlike schemes, in contrast to chain-and tree-like ones, yield extremely precise approximations for rather coarse abstractions. D. Klink has been funded by the DFG Research Training Group 1298 (AlgoSyn) and the EU FP7 project QUASIMODO. A. Remke has been funded by the NWO project MC=MC (612.000.311) and by 3TU.CeDiCT.