There is a considerable amount of research currently focusing on examining different types of degradation processes that occur within technical systems. In most cases, these processes are analyzed separately, and their combined effect on the system's overall residual life is reduced to selecting the most intense process, often referred to as the “weakest link”. This approach significantly simplifies all aspects of every degradation process, which, in turn, can lead to overestimated forecast results. The article presents a method for estimating an object's residual life under the influence of several concurrent degradation processes, each with different impact proportions and occurring at different temperatures. The method involves determining the average rate of the generalized degradation process and its coefficient of variation using a probabilistic-physical model with the Diffusion Monotonic failure distribution. The DM-distribution is formalized based on a diffusion-type Markov process with a fixed rate that approximates statistical failure data in technical systems. Considering the concurrent influence of several degradation processes and different temperature conditions, the contribution proportions of each process to the generalized degradation have been determined and applied. This method provides a more accurate assessment of an object's overall residual life compared to methods that consider only the dominant processes. Accurate estimation of residual life values will help minimize operational expenses by adjusting the frequency of technical inspections and providing a proper assessment of the examined objects’ service life.