A method for predicting a remaining lifetime of an electrical component of an electrical circuit, the electrical circuit being part of a building management device; whereby the method comprises: - estimating (S1) two or more temperatures of the electrical component by using a trained machine learning model of the electrical component that is trained based on training data comprising a plurality of data sets, wherein each data set of the plurality of data sets comprises: - a real temperature of the electrical component at a respective time of an operation of the electrical circuit, in association with - a plurality of parameters of the electrical circuit at the respective time, wherein the plurality of parameters comprises one or more physical parameters of the electrical circuit and/or one or more operation parameters of the electrical circuit; - estimating (S1) each temperature of the two or more temperatures at a respective time by inputting (S11) a plurality of parameters, that are of the same type as the plurality of parameters used in the training data, for the respective time to the trained machine learning model that computes(S12) the estimated temperature of the electrical component at the respective time based on the plurality of parameters for the respective time; - generating (S2) a temporal course of temperature of the electrical component based on the two or more estimated temperatures; and - computing (S3), based on the temporal course of temperature of the electrical component, an indicator for the remaining lifetime of the electrical component. - estimating (S1) two or more temperatures of the electrical component by using a trained machine learning model of the electrical component that is trained based on training data comprising a plurality of data sets, wherein each data set of the plurality of data sets comprises: - a real temperature of the electrical component at a respective time of an operation of the electrical circuit, in association with - a plurality of parameters of the electrical circuit at the respective time, wherein the plurality of parameters comprises one or more physical parameters of the electrical circuit and/or one or more operation parameters of the electrical circuit; - a real temperature of the electrical component at a respective time of an operation of the electrical circuit, in association with - a plurality of parameters of the electrical circuit at the respective time, wherein the plurality of parameters comprises one or more physical parameters of the electrical circuit and/or one or more operation parameters of the electrical circuit; - estimating (S1) each temperature of the two or more temperatures at a respective time by inputting (S11) a plurality of parameters, that are of the same type as the plurality of parameters used in the training data, for the respective time to the trained machine learning model that computes(S12) the estimated temperature of the electrical component at the respective time based on the plurality of parameters for the respective time; - generating (S2) a temporal course of temperature of the electrical component based on the two or more estimated temperatures; and - computing (S3), based on the temporal course of temperature of the electrical component, an indicator for the remaining lifetime of the electrical component. <EOS>