A method of analysing the quality of a weld bead in a welding zone, 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, thereby melting the material of at least two or more metal pieces (M1, M2), the method comprising the steps of: - monitoring said welding zone via a thermal camera, wherein said thermal camera provides a sequence of thermal images, and wherein a given area (SA') in said thermal image corresponds to said welding zone; - 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 that identify the shape of the cooling curve; and - using said parameters 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 via a thermal camera, wherein said thermal camera provides a sequence of thermal images, and wherein a given area (SA') in said thermal image corresponds to said welding zone; - 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 that identify the shape of the cooling curve; and - using said parameters 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 that identify the shape of the cooling curve; and - using said parameters 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).