The principle of lean manufacturing is the elimination of all wastes within a company and continuous development of more effective and efficient production.The manufacturing industry is constantly trying to improve in these areas and successfully implementing lean manufacturing has been shown to significantly improve quality and production rates,whilst reducing wastes in the form of cost,time,energy and space.Two of the most common problems when attempting to implement lean manufacturing are the correct identification of problems within a company and the misuse of lean tools when addressing problems.This paper proposes a model to identify the strengths and weaknesses of a case study company within the steel industry in terms of capabilities the company possesses to achieve leanness and to identify the suitable lean tools to improve these capabilities.The paper reviews previous models for analysing lean manufacturing within various manufacturing industries,highlighting the advantages and disadvantages of each model.A model based on neural networks is then proposed in order to identify the current state of the company with regards to lean manufacturing,possible areas for improvement and lean tools that could be used to manage these improvements.Questiormalres,site visits and interviews were conducted to obtain information for analysis.The model identifies the capabilities necessary for the company to achieve leanness and the appropriate lean tools to develop these capabilities.The results given are specific to the case study company but it is applicable to companies in other industries.