Bayesian approach is the most important methods that used in the statistical analysis, so we have
studied in paper this approach by using two of the Sigmoidal growth models, where those models
are more using to represent the growth phenomena. The researchers focused on three of prior
functions (Informative, Natural Conjugate, and the function that depends on previous
experiments) to use it in the Bayesian method. The goal of this study is to estimate the
parameters of the growth models by using Bayesian method, and compare it with the Least
squares method. For verifying the goal has been used the simulation technique where generated
random samples with known parameters. It has been shown from the computational results that
the Bayesian method is better than the Least squares method to estimate the Sigmoidal growth
models.