Retinoblastoma is an embryonic intraocular tumor arising in the retina of the eye. It is a dangerous tumor that can damage the eye and its surrounding components. Chromosome 13q14.1-14.2 is the cytogenetic location of the RB1 gene. As a result, early identification of Retinoblastoma in children is essential. Over the last few decades, Retinoblastoma treatment has improved with the goal of not only saving life and the eye but also optimizing residual vision. In oncology, machine learning approaches used to predict cancer patient treatment outcomes include data collection and preprocessing, text mining of clinical literature, and constructing prediction models. This paper discusses recent advances in the management of Retinoblastoma, as well as data preparation and model construction for identifying patterns between Retinoblastoma clinical factors and predicting therapy success using machine learning.