Cloud Computing has become a popular choice with the magnified evolution to facilitate various service provisioning to users, and the resources are dynamically configurable and accessible from anywhere. Besides maintaining interoperability between heterogeneous platforms, the services get provisioned over the internet. The service discovery is a critical phase when the clouds cooperate in providing various business opportunities. Selecting cloud services is vital to ensure efficient migration in cloud environments. If cloud service selection is inappropriate, the customer may face vendor locked-in issues, portability, and interoperability problems, significant obstacles to adopting cloud services. A new meta-brokering model is proposed to avoid the complexities mentioned before. The full rank ordering recommendations using the Stable Preference Ordering Towards Ideal Solution (SPOTIS) method enables the cloud users to decide and port services selectively and efficiently based on the weighted Decision Rank model with QoS analysis for service discovery along with distance criteria evaluated using the geographical location of Cloud Solution provider (CSPs). The proposed approach demonstrates the effectiveness of the combination of the Haversine and SPOTIS hybrid model and how SMI attributes affect the ranking recommendations. Our approach observes higher accuracy and outperforms other ranking methods for better service discovery.