The identification of white tea mainly relies on sensory evaluation and mass spectrometry methods, which have drawbacks such as strong subjectivity and complex analysis. Thus, this study established a novel approach based on colorimetric indicator displacement assay (IDA) sensor to achieve rapid and accurate white tea identification. Cost-effective dyes and phenylboronic acids with different substituents were selected as the indicator and receptor, respectively. A color-signal-responsive IDA sensor array was constructed to enable the rapid and sensitive identification of white tea. Additionally, three supervised pattern recognition algorithms were utilized to process image data. The results demonstrate that combining the IDA sensor with the random forest algorithm accurately differentiates white tea samples by origin and type, achieving a 100% recognition accuracy in both training set (n = 84) and prediction set (n = 56) when ntree = 1000. This work offers an economical and efficient method for the rapid identification of white tea products.