This research investigates the design and development of shape-morphing structures using smart materials, including hydrogels, Shape Memory Polymers (SMPs), and Shape Memory Alloys (SMAs), with applications in soft robotics. By leveraging the unique properties of these materials, the study aims to develop adaptive and responsive structures capable of controlled deformation, providing solutions for robotics, biomedical devices, and adaptive engineering systems. The main research question guiding this study is: ”How can smart materials be used to develop a shape-morphing structure applied to soft actuators?” To address this research question, a theoretical foundation was laid, and modelling techniques for shape-morphing structures using smart materials specifically hydrogels, SMPs, and SMAs were explored. These materials enable controlled and reversible deformations in response to external stimuli, making them ideal for applications in soft robotics, aerospace, and biomedical engineering. The role of morphology in shaping deformation behaviour was examined, highlighting how geometric configurations influence structural adaptability. Finite Element Analysis (FEA) was introduced as the primary tool for modelling and predicting material behaviour, facilitating the optimisation of shape-morphing actuators. The research further investigates how smart materials can be structured, actuated, and combined to achieve efficient morphing while ensuring stability, functionality, and durability. Special emphasis is placed on bending deformation as a key performance indicator (KPI) for evaluating actuator efficiency. Hydrogels were extensively examined for their stimuli-responsive properties, particularly their ability to swell and deform in response to external factors such as temperature changes. Various hydrogelbased structures were modelled, including ball-to-ball setups, flexible fingers, can structures, and surface grids. The results highlighted the critical role of geometric arrangements in determining deformation characteristics—symmetrical designs facilitated smooth and predictable morphing, whereas denser frameworks provided controlled folding and structural integrity. Material orientation significantly influenced deformation directionality, while overall structure length impacted computational complexity without drastically affecting morphing efficiency. A maximum expansion factor of 1.37 in diameter and 2.59 in volume at 275 K was observed, demonstrating the potential for substantial volumetric change in shape-morphing applications. For SMPs and SMAs, structural configurations were explored to enhance shape-morphing efficiency. A key development was the integration of the intelligent building block into a cylindrical geometry, designed for precise and controlled deformation. Material properties were analysed to identify factors influencing mechanical response, and constitutive equations were implemented in Abaqus to simulate thermo-mechanical behaviour under various loading and thermal conditions. Geometric parameters, including block width (Bw), block height (Bh), segment ratio (Rs), and cylinder thickness (Ct), were systematically optimised, revealing key interactions that affect morphing performance. Taller and wider blocks increased bending, while higher segment ratios and thicker cylinders exhibited reduced deformation. A Design of Experiments (DoE) methodology confirmed that geometric tuning enhances shape-morphing effectiveness. This design also showed that the maximum bending angle achievable was 60.0 degrees. Additional studies on cylinder orientations relative to the actuation direction demonstrated that minor misalignments had minimal impact on bending performance. Various geometric alternatives, including square, circular, elliptical, and hexagonal shapes, were evaluated, though the intelligent building block remained the most effective for precise, scalable deformation. Multi-cylinder configurations demonstrated multi-directional morphing, expanding the versatility of these materials for dynamic applications. The integration of SMPs, SMAs, and hydrogels into a unified shape-morphing framework underscores the potential of smart materials for advanced robotic and engineering applications. This study not only provides a strong theoretical foundation for the controlled actuation of these materials but also presents practical design principles for their implementation in soft robotic actuators, bio-inspired devices, and adaptable structures. By bridging theoretical principles with experimental validation, this research lays the groundwork for future advancements in smart material-based technologies. Future studies should focus on further optimising material properties, exploring hybrid actuation mechanisms, and incorporating torsional deformation to expand the capabilities of shape-morphing structures. Additionally, integrating these systems with external control feedback and real-world testing will be crucial for transitioning smart material actuators from simulation to real-world applications, particularly in soft robotics and adaptive mechanical systems.