The aim of this work is to distribute generalized suffix tree construction, so the process is efficient in terms of time complexity and memory consumption. A distributed approach to constructing the suffix tree will allow working with large alphabets and very long strings that exceed the available memory capacity. In this work, an efficient and highly scalable algorithm for constructing generalized suffix trees on distributed parallel platforms was modeled. The experimental results proved that the modeled algorithm’s efficiency is no less than the before known Elastic Range algorithm (ERa) while out-performing ERa on specific data.