Censoring is very common in life testing experiments and reliability studies. Progressive first-failure-censoring and an adaptive progressive Type II censoring schemes will be a good choice in this situation. Also, record values and associated statistics are of great importance in several real life problems. There are a number of situations in which an observation is retained only if it is a record value. In this book, we propose different methods to estimate the parameters of the Burr-XII distribution using different censoring schemes and record values. We used the maximum likelihood estimator, different parametric bootstrap methods and we provide a Bayesian method to estimate these parameters as well as the coefficient of variation, the stress-strength reliability model and hazard functions. In the Bayesian method we propose two approaches to approximate the posterior: Lindley's approximation and the Markov chain Monte Carlo (MCMC) methods. Also, the statistical Bayesian predictions have been treated. Bayesian prediction intervals based on progressive first-failure-censored from Burr-XII as a formative sample are obtained and discussed