I have been using Hugin for sometime now. I had tried Netica earlier on as well as Microsoft's MSBNx, but did not pursue as I got comfortable with Hugin. I would appreciate if you could give me a quick feature difference [there - not there] between BayesiaLab and Hugin. I mainly use BBN's in the software engineering domain - CMMI Prediction models etc.
BayesiaLab is a software for manually editing Bayesian networks (as Hugin, Netica, GeNie, ...) and for data analysis and data mining with Bayesian networks (I do not have any other comparable software in mind :-)). It allows to tackle most of the data mining problematics (unsupervised, supervised, data clustering, variable clustering, probabilistic structural equations).
It also comes with a broad set of analysis and optimization tools.
You will find below a link that will give you the full technical specifications of BayesiaLab, listing all the features of that tool. I think this will help you comparing BayesiaLab with Hugin.