Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 11 1 2025 03 15 115 132 EN Tareef Fadhil Raham Warith Al-Anbiyaa University - Iraq Zaher Raham Nahrain university- Ministry of Higher Education and Scientific Research -Iraq Abdulkhaleq Ali Ghalib Al-Naqeeb Medical & Health Technology College, Baghdad-Iraq 2024 12 23 2025 03 03 Bachground :While the main advantage of the confidence interval is that it enables more precise evaluations when the risk for the outcome of interest is related to the cluster size, the predicted confidence interval width demonstrates the degree of variability in the future data instead. Methods : We present a novel algorithm to create an intra‐cluster robust neighborhood confidence interval and width for each cluster to rank the widths from the narrowest to the widest width to determine each cluster's predicted variability and evaluate the corresponding observed values. An example was developed that assesses the finite‐sample behavior of this new method. Results : Robust neighborhood intra-cluster predicted CI width was obtained   for interpreting results  of  binary unequal sizes data. Narrow confidence intervals CI bounds suggest the results are not subjected to a high degree of random variations. Conclusions: Intra-cluster predicted robust neighborhood CI and its corresponding width is a useful instrument in binary outcome unequal cluster sizes data as a method of analysis. https://jbe.tums.ac.ir/index.php/jbe/article/view/1548