The Birnbaum–Saunders distribution has been largely studied and applied because of its attractive properties. We introduce a transmuted version of this distribution. Various of its mathematical and statistical features are derived. We use the maximum likelihood method for estimating its parameters and determine the score vector and Hessian matrix for inference and diagnostic purposes. We evaluate the performance of the maximum likelihood estimators by a Monte Carlo study. We illustrate the potential applications of the new transmuted Birnbaum–Saunders distribution by means of three real-world data sets from different areas.