By estimating the ideal points for the Justices of the Chilean Supreme Court (public law chamber, period 2009-2018), this research attempts to identify coalitions inside the Court and provide a measurement to predict the justices’ behavior. To this end, we followed Martin & Quinn (2002)’s method for studying the U.S. Supreme Court, applying an IRT model that allows to generate judges’ ideal points via a MCMC method to fit a Bayesian measurement model of ideal points for judges. The Chilean Supreme Court composition is substantially less stable than its counterparts in the U.S. or Europe, its workload is significantly higher and the rate of split decisions is considerably lower. Thus, the Court’s design poses challenges to study covariate effects on split decisions. The flexibility of this specification, to provide answers to different questions in the Chilean context, is discussed.