We constructed a database of layered intercalation compounds and successfully developed a regression equation to predict intercalation energy of layered intercalation compounds based on two properties of the intercalant: ∆𝐺 °f,M 𝑛 and the inverse of 𝑟 M 𝑛. We investigated the coefficients for the equation, demonstrating their prediction using machine learning approach. This enables the estimation of intercalation energy without first-principles calculations.