Tolerance allocation is a design tool that is proven crucial for enhancing the cost effectiveness and productivity of manufacturing systems. The growing implementation of additive manufacturing (AM) with its unique characteristics requires novel tolerance allocation methodologies to be developed. More specifically, many of the assumptions in traditional tolerance allocation methods such as normality assumption, a priori known probability density function of data, and symmetricity of tolerances cannot be seamlessly applied to AM processes. Furthermore, as the obtained dimensional errors of components in AM processes are significantly affected by the decisions made during the manufacturing stage (e.g., selected process, material, layer thickness, and build direction), the manufacturing parameters need to be jointly considered for allocating feasible and optimum tolerances during the product design phase. In this paper, a methodology for joint dimensional tolerance allocation and manufacturing of assemblies fabricated by AM processes is proposed based on the asymmetric distribution of errors and considering assembly requirements, namely, specification and confidence level. The bootstrap statistical technique is used to estimate the unknown population’s statistics. A cyclic optimization approach is adopted to tackle the formulated problem. The numerical examples are provided to illustrate the effectiveness of the proposed method. Note to Practitioners —Tolerance allocation is an important design task with significant impacts on cost and product quality. As the application of additive manufacturing (AM) for fabricating practical products (especially in critical industries) is increasing, it is important to develop the design and manufacturing standards and guidelines for both designers and manufacturers. Currently, there is a lack of tolerance specification standards and process capability evaluation of different AM processes. As a result, trial and error approaches are usually adopted to determine the feasible tolerances and cost-effective process plans, which are time-consuming (especially due to the slow production speed of AM) and require extensive efforts. In this paper, a methodology is proposed where the design and manufacturing decisions for assemblies with AM components can be made concurrently in a cost-effective way.