Given a system of multiple random variables, a new measure called the "L"-multivariate association coefficient is defined using (conditional) entropy. Unlike traditional correlation measures, the L-multivariate association coefficient measures the multiassociations or multirelations among the multiple variables in the given system; that is, the "L"-multivariate association coefficient measures the degree of the association for the given system. The "L"-multivariate association coefficient for the system of two random variables is also called the "L"-bivariate association coefficient. The association measured by the "L"-multivariate association coefficient is a general type of association, not any specific type of a linear or nonlinear association. Unlike the K-dependence coefficient, which is an asymmetrical measure, the "L"-multivariate association coefficient is a symmetrical measure. A direct application of the "L"-multivariate association coefficient is in variables selection or variables reduction. This paper also explores the relationship between the "L"-multivariate association coefficient and the "K"-dependence coefficient.