Woodworking is among the most dangerous activities with manifold risks to occupational safety and health of operators. Most of these risks are associated with the design of woodworking equipment. In this regard, the identification of woodworking equipment hazards (WEHs) is essential for improving safety. However, collective the identification and assessment of WEHs is not yet attempted in the woodworking literature, especially in the context of a developing country whose woodworking sector is more exposed to these risks. To address this gap, this paper employs a double triangular fuzzy Delphi method (FDM) in conjunction with the fuzzy Best-Worst method (F-BWM). The FDM was employed to select relevant WEHs, which are collectively sourced from previous literature, while the F-BWM is used to rank the relevant WEHs. The findings of this paper show that the risks posed by lack of "kickback safeguards" are the most important, while the risks posed by inadequate "maintenance functions" are the least important. The proposed algorithmic framework of this paper can help managers, occupational safety and health professionals, and woodworking firms in developing countries like the Philippines to build the capability they need to address WEHs and, to some extent, improve safety practices in the woodworking industry.