The implementation of Road Traffic Noise predictive Models (RTNMs) is crucial in order to be able to predict noise in urban areas strongly affected by vehicular traffic. These RTNMs can have in input a small or large number of inputs, according to the implemented function. Among these inputs, honking cannot be neglected in some specific areas in which drivers are used to horn in traffic jam or in proximity of intersections or other vehicles. In this paper, starting from a field measurement campaign in India, the authors highlight the shortcomings of standard RTNMs, that are not able to include random noisy events such as low or high pressure honking. Once the differences will be evaluated, the contribution of honking will be estimated and added to the predictions, to achieve a new model that is able to provide results in good agreement with field measurements.The implementation of Road Traffic Noise predictive Models (RTNMs) is crucial in order to be able to predict noise in urban areas strongly affected by vehicular traffic. These RTNMs can have in input a small or large number of inputs, according to the implemented function. Among these inputs, honking cannot be neglected in some specific areas in which drivers are used to horn in traffic jam or in proximity of intersections or other vehicles. In this paper, starting from a field measurement campaign in India, the authors highlight the shortcomings of standard RTNMs, that are not able to include random noisy events such as low or high pressure honking. Once the differences will be evaluated, the contribution of honking will be estimated and added to the predictions, to achieve a new model that is able to provide results in good agreement with field measurements.