The use of fuzzy numbers and their extensions, especially neutrosophic fuzzy numbers, is inevitable to express the value of the parameters of optimization problems derived from the real world. In this regard, the comparison and ranking of neutrosophic fuzzy numbers as one of the main research topics that can provide a suitable decision to solve optimization problems is of interest to researchers. In this study, we introduce a parametric approach to rank single value trapezoidal neutrosophic numbers which are based on decision–maker aspiration level for degree of the truth membership function and selecting appropriate levels for non-indeterminacy and non-falsity–membership functions. A prominent feature of this method is its high flexibility, which is due to the consideration of acceptable levels for evaluation by the decision maker. Therefore, in most decision issues, it can be used to determine the preferred option. Also, some theorems and reasonable properties are given to demonstrate the effectiveness of our proposed parametric approach. Furthermore, in an example of data envelopment analysis model with neutrosophic information the validity and applicability of the suggested method are examined.