Abstarct: In reliability analysis, accelerated life testing is the most common way to assess a product’s life. Under such test settings, products are tested ‎at higher than usual levels of stress to induce early failure. The goal of accelerated life analysis is to utilize the test data to extrapolate a ‎product’s life distribution and its associated parameters at a normal stress level. The current study introduces the geometric process model for the analysis of accelerated life testing with an weibull life ‎distribution under constant stress. By assuming that the lifetime under increasing stress levels forms a geometric process, we ‎derive the maximum likelihood estimators of the weibull parameter under three different censoring schemes: no ‎censoring, Type I and Type II censoring. For each censoring type, we also derive confidence intervals for the parameters using ‎both asymptotic distribution and the parametric bootstrap method. The performance of the estimators is evaluated by a‎ simulation study with different pre-fixed parameters.