  Accurate estimation such as cost estimation, quality estimation and risk
analysis is a major issue in management. We propose a patent pending soft
computing framework to tackle this challenging problem. Our generic framework
is independent of the nature and type of estimation. It consists of neural
network, fuzzy logic, and an algorithmic estimation model. We made use of the
Constructive Cost Model (COCOMO), Analysis of Variance (ANOVA), and Function
Point Analysis as the algorithmic models and validated the accuracy of the
Neuro-Fuzzy Algorithmic (NFA) Model in software cost estimation using
industrial project data. Our model produces more accurate estimation than using
an algorithmic model alone. We also discuss the prototypes of our tools that
implement the NFA Model. We conclude with our roadmap and direction to enrich
the model in tackling different estimation challenges.
