In this article we present the concept of green simulation, which views simulation outputs as scarce resources that should be recycled and reused. Output recycling, if implemented properly, can turn the computational costs in an experiment into computation investments for future ones. Green simulation designs are particularly useful for experiments that are repeated periodically. In this article we focus on repeated experiments whose inputs are observations from some underlying stochastic processes. Importance sampling and multiple importance sampling are two particular output recycling implementations considered in this article. A periodic credit risk evaluation problem in the KMV model is considered. Results from our numerical experiments show significant accuracy improvements, measured by mean squared errors, as more and more outputs are recycled and reused.