Parametric estimation plays a pivotal role in modeling reliability and survival data under complex censoring schemes. This study focuses on the estimation of parameters in flexible Weibull extension models when facing progressive Type-II censoring. The flexible Weibull extension is a versatile distribution capable of capturing a wide range of failure patterns. We propose an estimation method that harnesses the power of maximum likelihood estimation in conjunction with progressive Type-II censoring. Simulated and real-world data are employed to evaluate the method's performance, demonstrating its effectiveness in accurately estimating the parameters of the flexible Weibull extension model under this challenging censoring scenario.