Fisheries are one of the renewable resources that play a significant role on the livelihood of many rural and urban communities. Despite these, the sector is yet underdeveloped in Ethiopia and the fish value chain was not well addressed in Lake Tana. This study was carried out in Lake Tana during the 2022 season with four objectives: (1) to map the fish value chain, (2) identify actors and their roles, (3) to analyze the market margin of the actors along the fish value chain, (4) to identify factors that affect the quantity of fish market supply, and (5) to determine the factors affecting value addition participation and intensity. A three stage sampling procedure was adopted to randomly select the respondents from fishermen, fish traders, hotel and restaurant and consumers. The primary quantitative data were collected from 226 fishermen and 34 from traders, hotel and restaurants, and consumers. Descriptive statistics and econometric models, such as multiple linear regression with ordinary least square (OLS), double hurdle (DH), and multivariate probit models were employed for data analysis. The results reveal that input supplier, fishermen, wholesalers, retailers, collectors, cooperatives, vendors, hotels and restaurants, and consumers were the primary actors along the fish value chain. In all cases, hotels and restaurants followed by wholesalers have received the highest profit margin. The OLS result showed that education level, fishing experience, training, and market information have positive influence on fish market supply. On the other hand, farm land, engagement in fishing activity, boat type, market place problem, cold storage problem, and price fluctuation influenced the fish market supply negatively. According to the DH model result, boat type, fish catch/day and fishing experience found to have a positive and significant influence on the intensity of value addition. Whereas, total farm land, cold storage problem and labor cost affect the intensity of value addition negatively. The result of multivariate probit model indicated that education level, total farm land, boat type, engagement in fishing activities, market information, fish catch/day, and distance from landing site to main fish market significantly affected the fish market outlet of the fishermen. All these, suggest that fishery sector have several bottlenecks which needs intervention to better utilize the resources in the future.