Abstract: Embodiments are generally directed to systems and methods for generating resource deployment predictions using an ensemble machine learning model. An ensemble machine learning model trained or configured by an aggregated data set can be provided, where the aggregated data set includes data about resources deployed in enterprise deployment scenarios aggregated from a plurality of enterprise sources. Data about a first resource can be received including natural language data and numeric score data. A matching score between the first resource and a first enterprise deployment scenario can be determined based on a matching between natural language data descriptive of the first resource and natural language data descriptive of the first enterprise deployment scenario. Resource deployment parameters can be predicted using the ensemble machine learning model based on the determined matching score and the received numeric score data about the first resource.