Forecasting of scrapped products to recycling poses severe problems to remanufacturing companies due to uncertainties in timing and quantities of returns. A method is suggested combining a simulation approach with fuzzy reasoning. The prediction model presented here is based on life-cycle data (e.g., sales figures and failures) and impact factors (e.g., lifetime, wear and tear, usage intensity). First, these data serve to develop a simulation model, which consists of sub-models describing sales, failures, usage and returns, respectively. Furthermore, the forecasting approach will be extended by a fuzzy component introducing expert knowledge into the model design to obtain more accurate forecasting results. An empirical study has been applied using life-cycle data of photocopiers to forecast the returns. The results of this study are presented in this chapter as well.