We define the generalized Weibull model as an extension of the Rayleigh and the Pillai/Nair software manpower estimation models. All three models are evaluated, through cross-validation, using one particular set of manpower data. Analyses are conducted to evaluate and compare the overall as well as the early stage predictive capabilities of the three models. For the full manpower data set, the generalized Weibull model substantially outperforms both the Rayleigh and the Pillai/Nair models. It also outperforms both of the other models for the first half year of manpower data, but the improvement over the Pillai/Nair model is not substantial. However, in this case, both of these models substantially outperform the Rayleigh model indicating that the Pillai/Nair model can track early manpower build-up better than the Rayleigh model. We choose some of the parameters of the generalized Weibull model adaptively by minimizing the standard prediction error for deleted manpower predictions, thereby guaranteeing that it provides manpower estimates at least as good as those generated by submodels like the Rayleigh and Pillai/Nair models. Our analyses demonstrate that these benefits can in fact be substantial, recommending its use over the Rayleigh and Pillai/Nair models.