A method of analysing the quality of a weld bead in a welding zone (SA), said weld bead being generated by means of a continuous welding operation, wherein an energy beam emitted by a source with corresponding welding head follows a welding path (SP), thereby melting the material of at least two or more metal pieces (M1, M2), the method comprising the steps of: - monitoring said welding zone (SA) via a thermal camera , wherein said thermal camera provides a sequence of thermal images (IMG), and wherein a given area (SA') in said thermal image (IMG) corresponds to said welding zone (SA); - dividing said area (SA') into a plurality of sub-areas (A1, ..., An) and determining for each sub-area (Ai) a respective temperature (Ti) as a function of the values of the pixels within the respective sub-area (Ai); characterized in that the method further comprises the steps of: - during a learning step wherein a plurality of welding operations are performed both with sufficient quality and with insufficient quality, monitoring via said thermal camera the temperature evolution ( Ti ( t )) of each sub-area ( Ai ) during each welding operation; - during a training step , processing the temperature evolutions ( Ti ( t )) monitored during said learning step for training a classifier configured for estimating a weld quality as a function of respective temperature evolutions ( Ti ( t )), wherein said processing the temperature evolutions ( Ti ( t )) comprises: - extracting from each temperature evolution ( Ti ( t )) a respective cooling curve and determining for each cooling curve a plurality of parameters (F) that identify the shape of the cooling curve; and - using said parameters (F) as input features for said classifier ; and - during a normal welding operating step , monitoring via said thermal camera the temperature evolution ( Ti ( t )) of each sub-area ( Ai ) during a welding operation and estimating via said classifier the respective weld quality ( S, C ). - monitoring said welding zone (SA) via a thermal camera , wherein said thermal camera provides a sequence of thermal images (IMG), and wherein a given area (SA') in said thermal image (IMG) corresponds to said welding zone (SA); - dividing said area (SA') into a plurality of sub-areas (A1, ..., An) and determining for each sub-area (Ai) a respective temperature (Ti) as a function of the values of the pixels within the respective sub-area (Ai); - during a learning step wherein a plurality of welding operations are performed both with sufficient quality and with insufficient quality, monitoring via said thermal camera the temperature evolution ( Ti ( t )) of each sub-area ( Ai ) during each welding operation; - during a training step , processing the temperature evolutions ( Ti ( t )) monitored during said learning step for training a classifier configured for estimating a weld quality as a function of respective temperature evolutions ( Ti ( t )), wherein said processing the temperature evolutions ( Ti ( t )) comprises: - extracting from each temperature evolution ( Ti ( t )) a respective cooling curve and determining for each cooling curve a plurality of parameters (F) that identify the shape of the cooling curve; and - using said parameters (F) as input features for said classifier ; and - extracting from each temperature evolution ( Ti ( t )) a respective cooling curve and determining for each cooling curve a plurality of parameters (F) that identify the shape of the cooling curve; and - using said parameters (F) as input features for said classifier ; and - during a normal welding operating step , monitoring via said thermal camera the temperature evolution ( Ti ( t )) of each sub-area ( Ai ) during a welding operation and estimating via said classifier the respective weld quality ( S, C ). <EOS>