This research is intended for developing innovative metallic connectors for wooden beam-to-column joints and estimating its structural performance in terms of rotational and shear behaviour. The first step is the design as well as the production of the metallic connector. The connector is made of aluminium and fixed onto wooden elements by means of self-tapping screws (STS). The profile and allocation of the aluminium connector differ from the commercial products. Based on the concept of traditional timber constructions in Taiwan and inspired by the research of Li et al. [1], the connector possesses dovetail profile. The connector comprises a series of holes for STS which are drilled in different angles into wooden components. The location and orientation of those holes contribute to maximise the number and length of the screws. The allocation of multiple connectors may improve joints’ rotational behaviour. A series of full-scale testing is intended for appraising the rotational and shear behaviour of the wooden joint composed of the aluminium connectors and STS. The testing rig and subsequent analysing processes derive from former publications such as the study by Leijten and Brandon [2]. The testing results demonstrate that the innovative connector can improve the resistance of the wooden joints. While the ultimate shear is about 13 kN, the moment capacity is about 2.1 kN-m. Meanwhile, the ductility from both rotational and shear tests is higher than 3.0. The failure modes reveal ductile characteristics of the connections. Prior to yield strength, the failure is mainly and only the deformation of aluminium connectors. Nevertheless, the dovetail prevents the connectors from detachment, mitigating the risk about brittle or unfavoured failure modes. These outcomes are considerable, compared to some commercial connectors [3]. The quantitative and qualitative results demonstrate the feasibility of the innovative connectors for timber joints. Finally, a diagram of the connector and reaction indicates the concepts about developing analytical models. Reference [1] Li, H., Lam, F., & Qiu, H. (2019). [2] Leijten, A. J. M., & Brandon, D. (2013). [3] Masaeli, M., Gilbert, B. P., Karampour, H., Underhill, I. D., Lyu, C. H., & Gunalan, S. (2020).