Our work contributes to investigate and estimate the degradation, altered bioactivity and color of Berberis crategina anthocyanins in different buffer systems and apple juice. Anthocyanins are glycosides of anthocyanidins, a subclass of flavonoids. These pigments impart red to blue coloration to fruits and flowers. Anthocyanins have antioxidant properties due to the positively charged oxygen atoms they contain. Chemical structure, enzymes, temperature, light, pH, oxygen, ascorbic acid, sugars, metals, sulfur dioxide, and copigmentation affect the stability of anthocyanins. In this study, it was primarily aimed to investigate the effects of temperature, time and pH on total anthocyanin content (TAC), total phenolic content (TPC), antioxidant activity (AA) and color of Berberis crataegina. Another aim was to estimate the TAC, TPC, AA, and color of Berberis based on temperature, time, and pH with ANN modeling. An artificial neural network (ANN) was used to predict the relationship between TAC, TPC, AA and color of Berberis crataegina and temperature, time, and pH for both apple juice and buffer solution. It was found that high temperature and low acidity increased anthocyanin degradation, while total phenolic content and antioxidant activity decreased. L* and h° were found to decrease and C* to increase due to anthocyanin degradation. The results indicate that pH is the most effective factor (73%) in prediction and that ANN performs better than a buffer solution for apple juice. The sum of square errors of the validation samples was 7.89 for buffer solution and 1.26 for apple juice. This study showed that the parameters studied can be successfully estimated using ANN