Parameter reduction can be treated as an effective tool in many fields, including pattern recognition. Many reduction techniques have been reported so far for soft sets, fuzzy soft sets and bipolar fuzzy soft sets to solve decision-making problems. However, there is almost no attention to the parameter reduction of neutrosophic soft sets. In this present paper we focus our discussion on the parameter reduction of neutrosophic soft sets as an extension of parameter reduction of soft sets and fuzzy soft sets. To do that, using the concept of indiscernibility relation, we first define the terms ‘dispensable set’ and ‘indispensible set’. We utilize these definitions to define the terms ‘decision partition’, ‘parameter reduction’ and ‘degree of importance of a parameter’ with a suitable example. Next we present an algorithm based on the concept of degree of importance and parameter reduction of a neutrosophic soft set. An illustrative example is employed to show the feasibility and validity of our proposed algorithm based on parameter reduction of neutrosophic soft sets in real life decision making problem.