Early detection of vascular function plays an important role in the prevention and treatment of cardiovascular diseases (CVDs). This paper reports the main studies of the effectiveness of fingertip temperature curve in digital thermal monitoring (DTM) for predicting CVDs, as well as the relationship between parameters from DTM and pulse wave velocity (PWV) detection. A total of 112 subjects [age (42.18±12.28) years, 50% male, 37 with known CVDs] underwent DTM and PWV detection. Results showed that most of parameters related to CVDs were from the declining stage of the digital thermal signal. Binary Logistic regression models were built, and the best one was chosen by ten-fold validation to predict CVDs. Consistency was great between the detection result of PWV and that of the Logistic model of DTM parameters. Parameters from DTM also contained information for early detecting of vascular stiffness. This study indicates that the fingertip temperature curve in DTM has a potential application for predication of CVDs, and it would be used to access vascular function in the initial stage of CVDs.