Method of determining a remaining time interval (RTI) until a measurement characteristic (MC) of a field device (FD) will have drifted outside of a predetermined maximum tolerance (T) and a service action is required, wherein the field device (FD) is measuring or monitoring at least one process variable of a medium in a process specific application (AP) of automation technology, comprising the steps of: Predetermining the maximum tolerance (T) wherein the measurement characteristic (MC is correlated or related to a measurement performance of the field device (FD), wherein the measurement performance of the field device (FD) in the process specific application (AP) is unacceptable if the measurement characteristic (MC) reaches or exceeds the predetermined maximum tolerance (T); Registering continuously the measurement characteristic (MC) of the field device (FD); Based on the registered measurement characteristics (MC) during a given time interval or based on continuously registered data related or correlated to the measurement characteristic (MC) of the field device (FD) during a past time interval (TI), estimating a lag time interval (LTI), wherein the estimated lag time interval (LTI) depends on the drift of the measurement characteristic (MC) of the field device (FD) in the process specific application (AP); Using a Monte Carlo Simulation or a method of Artificial Intelligence to, at the end of the estimated lag time interval (LTI) and based on the registered measurement characteristics (MC), determine the remaining time interval (RTI) until the measurement characteristic (MC) of the field device (FD) will have drifted outside the predetermined maximum tolerance (T) and the service action is required; Generating a message (M) informing of the remaining time interval (RTI) and Using a non-linear transformation (f(t)) of the determined remaining time interval (RTI) relative to the lag time interval (LTI) to determine a confidence level CL) wherein the confidence level (CL) provides information about the reliability of the determined remaining time interval (RTI) . Predetermining the maximum tolerance (T) wherein the measurement characteristic (MC is correlated or related to a measurement performance of the field device (FD), wherein the measurement performance of the field device (FD) in the process specific application (AP) is unacceptable if the measurement characteristic (MC) reaches or exceeds the predetermined maximum tolerance (T); Registering continuously the measurement characteristic (MC) of the field device (FD); Based on the registered measurement characteristics (MC) during a given time interval or based on continuously registered data related or correlated to the measurement characteristic (MC) of the field device (FD) during a past time interval (TI), estimating a lag time interval (LTI), wherein the estimated lag time interval (LTI) depends on the drift of the measurement characteristic (MC) of the field device (FD) in the process specific application (AP); Using a Monte Carlo Simulation or a method of Artificial Intelligence to, at the end of the estimated lag time interval (LTI) and based on the registered measurement characteristics (MC), determine the remaining time interval (RTI) until the measurement characteristic (MC) of the field device (FD) will have drifted outside the predetermined maximum tolerance (T) and the service action is required; Generating a message (M) informing of the remaining time interval (RTI) and Using a non-linear transformation (f(t)) of the determined remaining time interval (RTI) relative to the lag time interval (LTI) to determine a confidence level CL) wherein the confidence level (CL) provides information about the reliability of the determined remaining time interval (RTI) . <EOS>