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We introduce an R package that estimates decision thresholds in diagnostic settings with a continuous marker and two or three underlying states. The package implements parametric and non-parametric estimation methods based on minimizing an overall cost function, as well as confidence interval estimation approaches to account for the sampling variability of the cut-off. Further features of the package include sample size determination and estimation of diagnostic accuracy measures. We used randomly generated data and two real datasets to illustrate the capabilities and characteristics of the package.