A curve fitting method based on abstract convex estimations includes the following steps that supporting vectors begin to be built from two boundary points to form an initial supporting matrix, and the initial supporting matrix is used as a root to built a binary tree; supporting vectors are built for known data points, and the binary tress is updated according to a certain condition; a sampling step length is set, sampling is conducted within a definitional domain range of x, tree leaf child nodes to which sampling points belong are found out, and lower bound low estimators of a tree leaf child node zone to which the sampling points belong are calculated; all the sampling points are connected, and then lower bound saw tooth estimations of a curve to be fitted can be obtained; upper bound saw tooth estimations of the curve to be fitted can be obtained through the same method, and the curve which is obtained by averaging the upper bound saw tooth estimations and the lower bound saw tooth estimations is used as the curve to be fitted. The curve fitting method based on the abstract convex estimations has the advantages that calculated amount is small, the original data points can be reserved, and fitting efficiency and the accuracy rate are high.