<p>In the realm of circular economy, effective product life cycle management necessitates decision support systems capable of adapting to the dynamic and stage-specific variations in product demand and return rates. Current literature often assumes identical replenishment cycles throughout a product’s life, overlooking that demand and return rates fluctuate significantly across different life cycle stages. This paper addresses this critical gap by introducing a novel decision support system that integrates adaptive replenishment strategies tailored to each phase of the product lifecycle. Unlike traditional approaches, which reset demand rates at the beginning of each cycle of every stage, this study ensures continuity and reflects the practical progression of demand within and across planning horizons. A fuzzy modeling approach accommodates uncertainties inherent in finite planning horizons, enhancing the system’s robustness. Analytical findings reveal that during the growth stage, production periods must increase in arithmetic progression with successive replenishment cycles. Conversely, the maturity stage requires a longer remanufacturing period and shorter production cycles, with adjustments proportionate to return rates and inversely related to remanufacturing rates. Numerical results emphasize that indiscriminately accepting all returned items during the decline stage is suboptimal and should be strategically limited. This study’s innovative framework bridges the gap between theoretical assumptions and practical realities, providing actionable insights for production and remanufacturing planning in finite and uncertain planning horizons. By incorporating dynamic demand and return rates, this work offers a pioneering contribution to sustainable product life cycle management, paving the way for more realistic and effective strategies in circular economy settings.</p>