Currently various collection strategies are implemented in different parts of the world to collect End-of-Life (EOL) products. Since different collectors in the reverse logistics network will influence the performance of a collection strategy, a suitable collection program is required. The objective of this research is to find an optimum collection strategy to suit various environments by considering the costs and the environmental aspects of collection. To design optimum collection strategies, information on the rate of EOL product returns is essential. Therefore, a methodology is proposed to forecast the return of EOL products by considering product life, consumer behaviour and historical sales. This forecast model is then integrated into the collection strategy model. The integrated model is dynamically formulated to present the behaviour of different sets of strategies. Coloured Petri Net (CPN) approach is utilised in the forecasting and modelling of collection strategies. The results indicate that the integrated model will help practitioners in making decisions on implementing a suitable collection strategy for Reverse Logistics.