The microservice-oriented architecture (MSA) is an architectural style which involves organizing an application as of small independent services, each oriented towards one business functionality while being data autonomous. In pursuit of modernizing their software to take advantage of the Cloud, companies have been eager to migrate their monolithic legacy software towards an MSA. This migration necessitates an identification phase to reorganize classes around the monolith’s functionalities as a set of microservice candidates. However, most identification approaches fail to utilize the monolith’s internal multilayered architecture to identify those functionalities, and thus the microservices. As a consequence, ignoring the internal multilayered architecture increases the risk of identifying microservice by their technical layer which is recognized as a conceptual anti-pattern. In this paper, we explore the impact of the multi-layer architecture in monolithic applications during the identification to develop a semi-automatic approach that relies on it to identify an MSA. Particularly, we analyze the presentation layer to determine the endpoints of each business functionality of the monolith. From these endpoints, we apply a vertical decomposition to identify the necessary classes to implement each feature as a microservice. In the process, we also define the bounded context of each microservice during the vertical decomposition of the data-access layer. For the evaluation, we implemented a model-driven process and applied it on a set of varying open-source applications commonly used in the literature. We compared the results of approach with and without the reverse-engineering of the internal architecture to measure the impact of our approach on the identification of quality microservices. Using decomposition metrics (e.g., MoJoFM, c2c cvg ), we were able to measure a significant positive impact.