The book "Statistical Tools for Nonlinear Regression, Second Edition" offers comprehensive methods for analyzing data using parametric nonlinear regression models. This updated edition expands the content to include binomial, multinomial, and Poisson nonlinear models. Examples from agronomy and biochemistry demonstrate how these methods can be applied in practice. The focus is on presenting the methods intuitively rather than concentrating on theoretical foundations. Analyses are conducted using the free software nls2, which has been specifically updated for the new models in this edition. The software is implemented in S-PLUS and R, significantly facilitating the tasks of model building, estimation, and validation. Complex models can be easily described using a symbolic syntax, and there is the option to add parameter constraints to test nested hypotheses and compare multiple datasets.