Quantum computing represents a paradigm shift in computational science, offering the potential to solve complex engineering problems that are beyond the capabilities of classical computers. By leveraging principles such as superposition, entanglement, and quantum interference, quantum computers can process vast amounts of information simultaneously and perform certain computations exponentially faster than classical systems. This transformative capability has significant implications for engineering disciplines, including optimization, material science, structural analysis, fluid dynamics, and energy systems.This study explores the applications of quantum computing in solving complex engineering problems. It examines how quantum algorithms such as Shor’s algorithm, Grover’s algorithm, and quantum annealing can be applied to engineering challenges involving large-scale optimization, simulation, and data analysis. A descriptive research methodology supported by secondary data and a structured survey is used to analyze the potential and limitations of quantum computing technologies. The findings indicate that quantum computing has the potential to revolutionize engineering problem-solving by enabling faster computations, improved accuracy, and innovative solution approaches. However, the study also highlights several challenges, including hardware limitations, error rates, scalability issues, and the need for specialized expertise. Despite these challenges, ongoing advancements in quantum hardware, algorithms, and hybrid computing models are expected to accelerate the adoption of quantum computing in engineering applications. This research provides valuable insights into the future role of quantum computing in engineering and its potential to address complex, large-scale problems.