The dynamic nature of today’s construction industry compels construction partners to seek strategies to improve performance. This study introduces an updatingperformance evaluation model for that one previously developed by Goda (1999).Updating the model has been made for; 1) increase the number of studied years to nine years (1992-2000), 2) testing the effect of macro-economic and industry related factor on the performance evaluation of Egyptian construction companies. Theupdating of the model takes in to account the company-size effect on the performance evaluation of construction companies. Also. The study tested the validity of the ”Unsupervised Neural Network” technique to solve the problem. But this trial failedbecause this technique needs a large number of observations in the same year. This large number of companies was not available by any way. The model development aims to provide a proper tool for company’s manager, owners, shareholders, and funding agencies to evaluate the fmancial performance of construction companies. Inaddition, it helps company’s management to take the right financial decisions. It is developed based on Egyptian construction industry fmancial data for nine consecutive years (1992 - 2000). Three indices are developed: (1) company performance score(Se) using six fmancial ratios; (2) economy performance score (Se) and industry performance score (Si); and (3) performance index (PI). The developed model considers companies in four construction sectors: (a) general building construction;(b) heavy construction; (c) special trade construction; and (d) real estate construction.The fmal outcome of this study is a performance grade (G), which provides thefinancial situation of a construction company. This research is relevant to bothresearchers and practitioners. It provides models for practitioners’ usage to assesstheir companies and take the right decision to reform companies’ financial situation.In addition, it provides the researchers with regression models that they can build onand develop future researches in this subject.