Shape memory alloys (SMAs) are smart materials with remarkable functional properties, such as pseudoelasticity and the shape memory effect. Their engineering application, however, remains challenging due to the complexity of their thermo-mechanical response. This response is governed by solid-to-solid phase transformations that are highly sensitive to ambient conditions, in particular temperature and stress state. Moreover, manufacturing and processing routes (e.g., rolling, drawing, heat treatment) can induce microstructural features that lead to direction-dependent transformation behavior, giving rise to pronounced anisotropy in macroscopic experiments. In this talk, a macroscopic modeling framework for SMAs is presented that consistently accounts for elastic and inelastic thermo-mechanical coupling mechanisms and incorporates transformation-induced anisotropy. The proposed methodology is formulated in a general manner such that arbitrary anisotropic behavior can be reproduced, avoiding restrictions to specific, preselected anisotropy laws. This enables the model to be calibrated to different processing histories and material conditions within a unified framework. The predictive capabilities of the approach are assessed by comparisons with experimental results obtained from demanding loading paths and coupled thermo-mechanical tests. The results demonstrate high agreement between simulations and measurements, indicating that the model captures the essential features of the material response.