The data measured by the pitot tube (PT) is related to airspeed indication and flight safety. However, there are few methods to solve the problem of failure prediction and predictive maintenance of PT. This study proposes a method for predicting the remaining useful life (RUL) of the PT based on dynamic operating data. First, an exposure index (EI) characterizing the severity level of operating conditions is proposed based on multiple dynamic operating and environmental parameters, then a cumulative exposure model (CEM) is developed to calculate the cumulative exposure. Dynamic covariate information is incorporated into the time-to-failure distribution of PT through the CEM, the RUL distribution of the individual PT is then obtained by Monte Carlo simulation. A case study is carried out based on actual data of a commercial aircraft fleet and shows that the proposed CEM can effectively use historical aircraft environmental information and truncated failure data of the components. The relative error of the remaining life prediction is substantially improved compared to the traditional reliability analysis methods, which means that the proposed model can provide more reliable RUL results based on historical operating conditions, providing better support for PT risk assessment and condition-based maintenance decisions.