This paper outlines the design of an acceptability judgment experiment, with a particular emphasis on power calculation. The experiment aims to determine whether there is a significant difference in the acceptability of a specific type of Japanese sentence when spoken in two distinct contexts. A central challenge in the experiment’s design is determining the appropriate sample size needed to detect these differences with sufficient power, typically set at 80% according to statistical convention. Given the limited literature on this specific Japanese phenomenon and the lack of relevant statistics on acceptability judgments, accurately estimating the sample size is difficult. To address this, the paper conducts a simulation using a custom dataframe and a linear mixed-effects model. This approach helps to avoid underestimating the necessary sample size, thereby reducing the risk of Type II, Type M, and Type S errors.