Temperate fruit trees require chilling for rest completion, followed by sufficient heat accumulation for onset of growth and bloom. The application of phenological models to predict bloom dates has been widely used in orchard management. Examples of such application include selecting adapted cultivars less prone to early bloom, predicting needs for frost protection, and preventing damage from late spring freezes. This study merged the Utah (chill) and ASYMCUR (forcing) phenological models by combining chill units and heat units (measured in growing degree hours) to predict bloom dates of tart cherries (Prunus cerasus L.) in Utah and Michigan, the top producing states of the USA. It was found that the modified Utah model improves the estimation of chill units compared with the original one, while the original Utah model may still be suitable for use in the colder winter of Michigan (with its later bloom dates than Utah). The combined models were applied with the temperature predicted by the Climate Forecast System v2 (CFSv2) model. The prediction was applied twice a month, starting from 1 February to 1 May. The Utah-ASYMCUR model using the forecasted temperature from CFSv2 exhibits subseasonal performance in predicting the bloom dates for 6 weeks in advance. The prediction can offer growers a way to mitigate extreme climate anomalies.