The load spectrum is the foundational data for reliability tests that simulate actual working conditions. Determining typical working conditions and accurate load extrapolation are the key to the load spectrum. This paper proposes a method for compiling the load spectrum of a reliability test program of CNC machine tools based on Weibull kernel function. The aforementioned method aims to address the issues commonly encountered in the load spectrum, such as complex factors that affect typical working conditions, heterogeneous load data of working conditions, and reliance on assumption distribution during load extrapolation. The method involves a determination process for typical working conditions using the Weibull kernel function and a non-parametric load extrapolation method based on kernel function. Firstly, this paper proposes a kernel density estimation method based on Weibull kernel function to address the issues of probability density contribution value deviation caused by the inconsistency between the conventional kernel function symmetry and the off-peak characteristic of load. The approach is based on the physical meaning and generalization of the Weibull distribution parameters and is used to determine the typical working conditions of CNC machine tools. Secondly, this paper proposes a nonparametric rainflow extrapolation method for cutting loads of CNC machine tools based on two-dimensional kernel density estimation. The approach takes advantage of the nonparametric rainflow extrapolation method and considers the characteristics of the cutting load. And the load spectrum of the three-dimensional cutting force of the CNC machine tool is constructed using the mean-range probability density distribution of the cutting load. Finally, the reliability test program loading spectrum of CNC machine tools is determined using the Conover ratio coefficient. Through case analysis, it can be known that the nuclear density estimation method proposed in this paper can improve the compilation accuracy of the load spectrum and has practical application significance.