Purpose : This dissertation is to investigate forecasting processes deployed in industries applying the “Pull” Approach which are confronted with an uncertainty linked to the variability of demand. We focus on upstream and/or downstream and/or internal forecasts to be implemented in “Pull” mode to improve the capacity planning of the company's activities. Forecasting tools, data, supply chain practices were examined and classified according to different variables and dimensions. After a literature review, some hypotheses were developed followed by a theoretical model linking the Resource-based view to the forecasting in the agile supply chain. Methodology : A literature review has been done for both understanding about the state-of-the-art in the fields and identifying research gaps for further research pathways. After the development of the hypotheses a theoretical research model was proposed. Findings: The research problem before the initiation of the master thesis was how to associate the pull mode in the forecasting of the supply chain, and after the literature review, it became evident that research in this regard clearly lacks a theoretical background and empirical research. These gaps were identified, and to bridge the gap in the body of research, we developed hypotheses and designed a model. Conclusion: After the contributions of the research, we see potential and promise in this research. By adding statistical tests to the current body of work, there could be a more definite indication about which relations among the constructs are positive or negative based on the answers of industries.