SummaryThis work aims at developing a class of nonlinear dynamical systems that can be converted into nonlinear observer normal forms, which support the well‐known high gain observer. This will be performed by means of the so‐called dynamics extension method, which explicitly supplies a set of auxiliary dynamics and changes of coordinates. In this work, the target nonlinear observer normal forms depend on both the output of the studied dynamical systems and the auxiliary variables involved in the definition of the extended dynamics. The method is proposed in a comprehensible way because it does not use differential geometry techniques, such as the Lie brackets calculations of some vector fields. The proposed class of dynamical systems has many practical applications such as epidemic systems, social networks, and so on. To highlight the effectiveness of this algorithm, it supplies an example based on the Maternal Immune Susceptible Exposed Infected and Recovered model.