The high-energy α particles produced by deuterium-tritium fusion are the primary heating source for maintaining high temperatures in future tokamak plasma. Effective confinement of α particles is crucial for sustaining steady-state burning plasma. The initial energy of α particles is 3.5 \text MeV . According to theoretical calculations, it takes approximately 1 second to slow down α particles through Coulomb collisions to an energy range similar to the energy range of the background plasma. In the slowing-down process, some α particles may be lost owing to various transport processes. One significant research problem is how to utilize α particles to effectively heat fuel ions so as to sustain fusion reactions in a reactor. Assuming local Coulomb collisions and neglecting orbital effects, a classical slowing-down distribution for α particles can be derived. However, considering the substantial drift orbit width of α particles and the importance of spatial transport, numerical calculations are required to obtain more accurate α particle distribution function. In this study, the particle tracer code (PTC) is used to numerically simulate the slowing-down process of α particles under different scenarios in the Chinese Fusion Engineering Test Reactor (CFETR). By combining particle orbit tracing method with Monte Carlo collision method, a more realistic α particle distribution function can be obtained and compared with the classical slowing-down distribution. The results show significant differences between this distribution function and the classical slowing-down distribution, particularly in the moderate energy range. Further analysis indicates that these disparities are primarily caused by the strong radial transport of α particles at these energy levels. The research findings hold profound implications for the precise evaluating of ability of α particles to heat the background plasma. Understanding and characterizing the behavior of α particles in the slowing-down process and their interaction with the plasma is critical for designing and optimizing future fusion reactors. By attaining a deeper comprehension of the spatial transport and distribution of α particles, it becomes possible to enhance the efficiency of fuel ion heating and sustain fusion reactions more effectively. This study establishes a foundation for subsequent investigations and evaluation of α particles as a highly efficient heating source for fusion plasmas.