After decades of experimental investigation, the dynamics howindividual cellsmove or deform-perfectly orchestrated for the creation and proliferation of tissue - remain partly unknown. In most recent years, the use of computational models, also called in silico experiments, has become a focus of interest. Due to their flexible scaling, compared to classical in vivo and in vitro studies, simulations can give important insights in the dynamics of cellular structures. We investigate Multi-Phasefield models for cellular structures, a versatile approach, capable of capturing complex changes in cell shape. Furthermore, it gives large flexibility in the modeling of cell-cell interactions and subcellular details like the propulsion machinery. The dynamics how these motility mechanisms create complex movement patterns on the tissue scale, will be a particular focus of this thesis. We compare four essentially different ways to introduce activity in Multi-Phasefield models, from movement driven by a random walk or the macroscopic shape of each cell towards a description of the subcellular machinery using either a polar or a nematic approach. For the different propulsion models, we investigate a variety of phenomena. Starting from the observation that the polar model creates collective motion, we observe that the resulting alignments resemble those of passive systems, expressed in Lewis’ and Aboav-Weaire’s law. Furthermore, we study a transition between solid and liquid state of the tissue, known to be important for many developmental processes. Additionally, we analyze the occurring patterns in the cellular alignment and flow, for systems in both confluence and confinement. Afterwards, we investigate the alignment of cell deformations with methods known from nematic structures. This reveals how the different propulsion mechanisms cause contractile or extensile behavior, classified by the movement of topological defects and the distribution of strain in their vicinity. At the end of this thesis, we show two extensions of themodels, capable of including growth and division of cells and generalizations towards curved manifolds as computational domains. Furthermore, we give an outlook on a possible roadmap for the future of Multi-Phasefield models in the description of cellular structures and their potential for a better understanding of the dynamics in the creation of life.