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When making decisions using multiple criteria, known as “multicriteria decision-making” (MCDM), it is essential to organize and address these challenges effectively. The Q-Neutrosophic Hypersoft Set (Q-NHSS) expands upon the Q-Neutrosophic Soft Set (Q-NSS) and integrates it with the Q-Fuzzy set, a two-dimensional information system. If we further divide the parameters into subparameters, we cannot use this technique to address these types of problems. This study introduces a new technique for this purpose, known as the Q-NHSS, and examines various Q-NHSS operations. These include Subset, Equality, Complement, Intersection, Union, AND, OR, Necessity, and Possibility operators. We provide suitable examples and demonstrate the implementation and validity of these operations. We then define the Q-NHSS aggregate operator and use it to create an algorithm for applying a Q-NHSS to decision-making problems with ambiguous and uncertain data. We then illustrate this with an example from a real-world application. Future decision-making, including personal selection, management issues, and numerous other issues, will heavily rely on the suggested processes to achieve more precision and accuracy.