Reliable forecasting of El Niño Southern Oscillation (ENSO) phases can minimize the risks in many critical areas including water supply, food security, health, and public safety on a global scale. In literature, several ENSO models are established but acquiring their accuracy is still questionable due to their chaotic behavior. Therefore, to confront this issue, the hybrid methodology of fractals and spline functions based on iterated function system and regression model is utilized in this article. To enhance their reliability and flexibility, an automated forecasting fractal algorithm with four free parameters and one risk factor (l_i,a_i ,ß_i ,?_i and d_i) is introduced. This method is an innovative approach in the field of climate science to not only depict versatile ENSO forecasting models but also analyze their peaks depends on their risk factor.