In this paper the research deals with appropriate methods of estimation and the important of using techniques estimating the parameter of nonlinear regression of linear regression with nonlinear regression models using robust methods .The possible of non-normal distribution and infinite variance in particular, has led to development of alternative estimation methods to the least square. Provided that one knows the generating distribution a well established procedure is the method of maximum likelihood, which has several optimal properties. Robust methods are known as resistant of abnormal values and other valuation of models assumption and appropriate for aboard category of distributor. A large number of other estimation methods aimed at achieving robustness have been suggested and a considerable body of literature has also been developed. Gonin and Money (1987), and the reference therein. Generally the robust estimators in the literature can be classified as M- estimators, L-estimators, or R- estimators. Probably most attention has been paid to the lestimators for other type estimators see judge et.al (1985) in the recent past. In this paper least absolute deviation methods using nonlinear with robust regression models has be studied Numerical illustration are also provided.