In the manuscript "A New Technique for Generating Distributions Based on a Combination of Two Techniques: Alpha Power Transformation and Exponentiated TX Distributions Family", a new distribution with five parameters, called "alpha power exponentiated Weibull-exponential distribution (APEWED)", is introduced based on a new technique developed by the authors that is a combination of two others: exponentiated TX and APT. The main goal is to introduce a new technique for constructing a family for generating some modified distributions with more flexibility in fitting data. Next, some properties of the proposed distribution are studied. The maximum likelihood method is used to estimate the unknown parameters of the model. Subsequently, these estimates are evaluated based on some simulation studies. The utility of the model is investigated through its application to two real data sets. The results show that the proposed distribution fits the data better than some other competing distributions that were being applied. Obtaining new distributions, through the most varied techniques, that best fit the real data is a subject that is in fashion, very intensively studied. That is what the author (s) in the Introduction tell us in which they present a numerous set techniques and respective authors, through a careful literature review. The authors' innovation in creating a new method should be highlighted here. The obtained distribution, having five relevant parameters, has the advantage of being flexible, with consequence of the many possible combinations of these parameters, allowing a myriad of forms. In particular, the various forms that the survival function, and the hazard rate function can take, make the family of distributions obtained from use particularly promising in the application to data in the field of Biology and Engineering. The "validation" of the obtained models is done, as usual, through the simulation methodology. As is evident, even though the results obtained and presented in the manuscript are interesting, it is not definitive. Only the intensive use in the future in the application to real and simulated data, can lead to the widespread acceptance of this family of distributions. Written in a scientifically rigorous manner, in readable English the manuscript can be published as is. However, a review of English is recommended in order to detect minor errors and to brush it up.