Seasonal forecasts are commonly issued in the form of anomalies as departures from average in a specified multiyear reference period (climatology). The model climatology is estimated as average of retrospective forecasts over the hindcast period. However, different operational centers providing seasonal ensemble predictions use different hindcast periods based on their own model climatology. In addition, the hindcast period of recently developed/upgraded newer models tends to shift to the recent years. In this paper, we discuss recent challenges faced by the APCC multi-model ensemble (MME) operations, especially changes in the hindcast period for individual models. Based on the results of various sensitivity experiments for the MME prediction, we proposed to change the hindcast period that is the most appropriate solution for the APCC operations. It makes the newly developed models join the MME and increase the total number of participating models, which facilitates the skill improvement of the MME prediction.