The present invention discloses a non-invasive blood glucose measurement method, applied to noninvasive blood glucose measuring instruments including measuring hosts and fingertip measuring probes, comprising pre-storing a random forest algorithm and a neural network prediction algorithm in the measuring host； measuring energy metabolism parameters of a fingertip of an individual to be measured and transmitting the parameters to the measuring host by the fingertip measuring probe； calling the random forest algorithm to predict the blood glucose type of the energy metabolism parameters of the fingertip of the individual to be measured and calling the corresponding neural network prediction algorithm to calculate the blood glucose value of the fingertip of the individual to be measured by the measuring host. The present invention also provides a fingertip-measuring probe. The non-invasive blood glucose measurement method disclosed in the present invention can be applied to non-invasive measurement of blood glucose, parameters related to energy metabolism of human body, healthy parameters of angiocarpy, etc.
