In this paper, we show how entropic sampling, 7-9 a density-of-states (DoS) estimation method developed in statistical physics, can elucidate the kinetic model with a limited number of samples. A key idea is to create a small number of weighted samples that approximate the probability density function in the outcome space (Figure ). By doing so, one can visualize and observe the relationship between variables with a limited computational cost. If random sampling is used, high quality points are not likely to be found due to small occurrence probability. Entropic sampling has a mechanism to sample from high quality regions to avoid this pitfall. Later on, the density function in the outcome space will be referred to as DoS following the terminology of statistical physics. Among multiple entropic sampling methods such as Wang-Landau method, 8 replica exchange samping 10 and transition matrix Monte Carlo, we choose entropic population annealing (EPA) due to simplicity and efficiency.