Recent advancements in information technology (IT) have made cloud computing one of the most prominent technologies. It is most favor- able for the bundle of services that it provides to its users. Since there is a wide range of cloud service providers (CSPs) with various services, it is chal- lenging for the user to select a CSP that can meet all of its requirements. In this paper, we propose a composite cloud service (CCS) model, which is handled by a cloud agent, to identify the best cloud services/criteria from a set of CSPs by considering the objective and subjective opinions collected from the cloud users’ feedback and reviews. Note that the cloud agent is an intermediary between the users and CSPs. Then the agent recommends the CSPs to assemble the identified services into unified group services to fulfill the users’ requirements. Our model calculates the integrated objective and subjective weight of alternatives for a set of criteria and determines the best alternative for each criterion. For this, the application of two multi-criteria decision-making (MCDM) techniques, namely method based on the removal effect of criteria (MEREC) and extended step-wise weight assessment ra- tio analysis (ESWARA), are used to calculate the objective and subjective weights, respectively. The proposed model is compared with the analytic hier- archy process-technique for order of preference by similarity to ideal solution (AHP-TOPSIS), TOPSIS-VlseKriterijuska Optimizacija I Komoromisno Re- senje (VIKOR), and SWARA-VIKOR to show its effectiveness.