Deploying 5G networks requires dynamic, scalable, and reliable infrastructures. As communication service providers work with Hyperscale Cloud Providers (HCPs), trust challenges arise due to the multi-stakeholder nature of 5G ecosystems. Choosing an HCP with the highest level of trustworthiness is essential for secure and resilient 5G deployment. Traditional probabilistic approaches struggle to accurately quantify trust, whereas fuzzy logic offers a nuanced evaluation of trust metrics. This paper proposes an Adaptive Layered Trustworthiness Assessment Model (ALTAM) for 5G services deployment, based on a hybrid fuzzy logic system (FLS) and an Adaptive Neuro-Fuzzy Inference System (ANFIS) learning layer. The proposed ALTAM is implemented across all its modules and then tested on three HCPs across twelve experimental scenarios. The performance evaluation and validation based on ALTAM confirm its reliability, effectiveness, scalability, and responsiveness to dynamic environments.