In this paper, we consider the prediction problem of the future failure times based on observed data from two-parameter Pareto-type distribution under Type-II right-censored samples. Different point predictors including best unbiased, maximum likelihood and conditional median predictors of the future failure times are obtained. The corresponding prediction intervals using pivotal quantity, conditional argument and shortest-length based method are also developed. The so-obtained point predictors and prediction intervals are compared via experimental numerical simulation. The optimality criteria considered for comparison purposes are prediction bias and mean square prediction error for point predictors and average length and coverage probability for prediction intervals. Real-life data representing the duration of the failure times of mechanical components as reported by Murthy (in: Wiley series in probability and statistics, Wiley, Hoboken, 2004) are analyzed for illustrative purposes
