While it is now widely accepted that new firms growth is essential for the foundation of economic dynamism, knowledge about this early growth is still scattered. Indeed, very little is known about how new firms grow and develop over time. What types of distinct growth patterns do those firms exhibit? How do these growth patterns and corresponding firms differ from each others in terms of development and strategic choices? To better understand the process of new firm growth, recent entrepreneurship research stresses that there is a strong need for a new conceptual scheme and new longitudinal research methods. This is actually one of the main entrepreneurship research challenges. In this context, our aim is to provide new insights regarding the process of new firm growth. In this research, we develop and test an original methodology allowing the empirical taxonomy of early growth trajectories across multiple sectors, integrating both the multidimensional and dynamic aspects of growth. Our approach applies principal component and cluster analysis to a large sample of firms, using financial and demographic data collected over time to identify in a systematic way distinct growth stages. We use then sequence analysis and a Markov chain approach to extract and compare the trajectories of individual firms over time. This allows the identification of a limited number of typical growth trajectories, which are adopted by the majority of firms in our sample. Finally, internal replication is performed to validate the growth trajectories identified and bivariate analysis is used to examine the link between the identified growth trajectories and the demographic characteristics of the corresponding firms. We have applied our methodology to a sample of 741 Belgian firms created between 1992 and 2002 and which have grown above micro-firm size. Our approach allowed identifying four distinct growth stages and seven typical growth trajectories, which remain valid for the six first years of the majority of the firms in our sample. This taxonomy of early growth trajectories is consistent with individual patterns already identified in the literature and appears not to be sector-dependent. The major contribution of this doctoral thesis is that, based on empirical evidence, early growth appears to be neither a continuous (or life cycle based) nor idiosyncratic (or completely random) process. It can be adequately described through a limited number of typical growth trajectories, valid across sectors. Thus, our research brings insight regarding how new firm evolve over time and therefore contributes to our understanding and appreciation of the heterogeneity of the growth trajectory phenomenon. Next, our research provides also an original methodological approach allowing the systematic analysis of growth trajectories, which deals with key limitations identified in the literature regarding the need for a multidimensional and dynamic study of growth across multiple sectors. Our findings indicate that this novel systematic approach is useful for taxonomy development and therefore contributes to reduce the gap between the complexity of new firm growth process and the standard approaches often mobilised to deal with it. Finally, while our findings provide empirical and methodological support in early development of new firms study, they also provide many implications to entrepreneurial research and practices. Further researches are needed to improve our understanding of the dynamic growth process of new ventures. It should explore which endogenous and exogenous factors might explain why a majority of start-ups follow the seven identified typical growth trajectories. It could be also highly relevant to refine our taxonomy by examining the relationship between innovative and technological sources and growth trajectories, both in high and low technological industries. Finally, we should test the accuracy of the proposed taxonomy across countries as well as beyond the early stage of new firm development.