Perishable inventory management contributes simultaneously to society and the economy, by reducing food wastage and capitalizing on the freshness of goods. For this reason, countless mathematical models have been developed for their effectiveness and costefficient management. Yet, the majority of these models can only optimize systems for a limited time frame, allowing for small gains in operations management, but failing to change the recurring patterns in inventory levels. System dynamics (SD) modelling shifts emphasizes these patterns and the recurring decisions that make them. Moreover, the framework has generated insight for other supply chain cases that could not have been derived from a short-term perspective. Thus, the current study now seeks to apply the SD framework in modelling perishable inventory systems, in designing policies that benefit the environment and the economy by reducing waste production and increasing the viability of goods reaching the customer. In particular, it evaluates the impact of opposing issuance policies (i.e. First-In-First-Out (FIFO) and Last-In-First-Out (LIFO)) on perishables to demonstrate the potential of SD in improving perishable inventory management. The simulated results share the sentiments of optimization models, that FIFO will ultimately generate less wastes and incur less material costs. Yet, the simulations also reveal implementing FIFO will result in larger fluctuations in inventory levels, which imply greater inconsistency in age-based quality. These suggest that LIFO would be preferable for quality-sensitive products, while FIFO would be preferable for cases sensitive to waste production. The current study demonstrates the efficiency of system dynamics in generating insight beyond that which can be derived from the existing mathematical models. Future studies may likewise extend this approach in the evaluation of policies on the use of technology in perishable inventory systems, which are the prevalent in present literature.