In this paper, we introduce a computational framework designed for the shape morphing of magneto-active polymers. The main ingredients encompassed within this paper are as follows: firstly, experimental characterization of the mechanical behaviour of the composite for various volume of rigid inclusions within the elastomeric matrix is carried out. This investigation unfolds both in the absence of magnetization and subsequent to the material undergoing magnetic saturation in diverse orientations. A critical facet of our work lies in the calibration of an invariant-based constitutive model, characterized by material frame-indifference and transverse isotropy. This calibration, accomplished through neural networks [1] and expressed in terms of invariants, distinguishes our approach from antecedent studies where the composite's purely mechanical response was assumed isotropic and independent of the influence of remnant magnetization [2]. In stark contrast, we substantiate the significance of accounting for the latter by incorporating a transversely isotropic contribution into the purely mechanical model. Furthermore, our computational framework integrates a multimaterial topology optimization methodology, employing the phase-field method [3]. This approach facilitates the selection of predefined discrete configurations for the remnant magnetisation that yield the optimal target shape morphing configuration when the material is subject to a given external magnetic field. The culmination of our efforts manifests in the examination of optimal results derived from remnant magnetization, subjected to laboratory testing. Research funded by Grants PID2022-141957OA-C22 by MCIN/AEI/10.13039/5011000110233 “ERDF A way of making Europe” and 21996/PI/22 Fundación Séneca REFERENCES [1] D. Klein, R. Ortigosa, J. Martínez-Frutos, A. J. Gil, Finite electro-elasticity with physics- augmented neural networks, Computer Methods in Applied Mechanics and Engineering, 400 (2022) [2] R. Zhao, Y. Kim, S. A. Chester, P. Sharma, X. Zhao, Mechanics of hard-magnetic soft materials, Journal of the Mechanics and Physics of Solids, 124 (2019), 244-263 [3] R. Ortigosa, J. Martínez-Frutos, A. J. Gil, Programming shape-morphing electroactive polymers through multi-material topology optimisation, Applied Mathematical Modelling, 118 (2023), 346-369