Lifetime (long-term) reliability has been a main design challenge as technology scaling continues. Time-dependent dielectric breakdown (TDDB), negative bias temperature instability (NBTI), and electromigration (EM) are some of the critical failure mechanisms affecting lifetime reliability. Due to the correlation between different failure mechanisms and their significant dependence on the operating temperature, existing models assuming constant failure rate and additive impact of failure mechanisms will underestimate the lifetime of a system, usually measured by mean-time-to-failure (MTTF). In this paper, we propose a new methodology which evaluates system lifetime in MTTF and relies on Monte-Carlo simulation for verifying results. Temperature variations and the correlation between failure mechanisms are considered so as to mitigate lifetime underestimation. The proposed methodology, when applied on an Alpha 21264 processor, provides less pessimistic lifetime evaluation than the existing models based on sum of failure rate. Our experimental results also indicate that, by considering the correlation of TDDB and NBTI, the lifetime of a system is likely not dominated by TDDB or NBTI, but by EM or other failure mechanisms.