<p>In this paper, a novel distribution called record-based transmuted exponential power is proposed. One of the notable advantages of the proposed distribution is that it serves as a flexible alternative to the exponential power and its modified ones, offering improved adaptability in modeling skewed or heavy-tailed real-life data structures since it has a decreasing and inverse bathtub curve hazard function shape. Nine different estimators are used to estimate the parameters of proposed distribution. Then, a comprehensive Monte-Carlo simulation study is designed to compare these estimators in terms of estimation procedure. Intensive simulation and optimization approaches are computationally necessary to obtain these estimators. Therefore, high-performance and parallel computing platforms are required to solve nonlinear equation systems. We utilize parallelized R software program routines for simulations and estimations. Also, three practical data examples are provided to assess the fits of suggested model as well as its competitor ones.</p>