For industries dealing with design and development of mechanical parts, the capability to predict the reliability is one of the important tasks to proceed ahead with further robust product development and meeting the customer requirements. This type of reliability prediction is performed using well established reliability standards, handbooks. Such methods are well established and proven for the parts that are manufactured by conventional manufacturing processes (CMP) due to past field failure data but as the design and development methods of product is evolving, evolution is being seen in case of various manufacturing processes across industries. Due to speed of production and cost benefits, industries are now preferring additive manufacturing (AM) process over CMPs. Additionally, AM process has other advantages such as better part strength, light weight, less material waste etc. The manufacturing processes play a significant role in achieving desired quality (reliability) target of a product. Hence, the failure rate prediction methods of product need to be evaluated as per the manufacturing processes, especially when limited or no field failure data available for AM manufactured parts. Thus, considering above limitation this paper proposes a methodology to predict the failure rate of the AM manufactured evolutionary parts. The proposed methodology develops a multiplying factor to base failure rate (BFR) that consider probability of manufacturing a healthy component (PMHC) as its primary function. The laser powdered bed fusion (LPBF) is the AM process used for the proposed methodology but the method could be applied for other AM manufacturing processes also.