  In order to gain a deeper understanding of complex systems and infer key
information using minimal data, I classify all configurations based on
classical probability, starting from the dimensions of energy and different
categories of configurations. By utilizing the principle of maximum entropy, it
is concluded that all possible configurations with the same energy have equal
probabilities of occurrence. By using different representations of high and low
energy, the emergence of a transition point has been inferred. Finally, I take
the Ising model as an example and calculate the transition point of the
thermodynamic phase transition, which is determined to be 2.25. This value is
very close to the simulation value obtained by Monte Carlo method, but I have
only consumed a small amount of computational resources in the process.
