This study aims to analyse the annual maximum (i.e., outlier or extreme) rainfall datasets, and also to detect potential trends and assess their significance for the Aegean region, Turkey. These datasets were analysed using the parametric Student's t-test, the nonparametric Mann-Kendall (MK) trend test, the Sen trend test, and a novel proposed approach in this present study. Moreover, a homogeneity test was applied to the datasets. The analyses were based on 60-year [1960-2019, except for Usak (1960-2015)] records at the eight meteorological stations. In this context, the findings showed that there was no statistically significant trend according to the Student's t-test and the MK test except for Afyonkarahisar. Sen test provided some different results from the Student's t-test and the MK trend test except for Kutahya, Manisa, Mugla, and Usak provinces. The novel approach provided some different results from the Student's t-test, Mann-Kendall (MK) trend test, and the Sen trend test. For example, there was a statistically significant increasing trend in the Student's t-test, Mann-Kendall (MK) trend test, and the Sen trend test for Afyonkarahisar. There was a statistically insignificant increasing trend in the newly developed approach at a 90% confidence interval with a two-tailed hypothesis test; therefore, this increasing trend especially for Afyonkarahisar should be considered in designing of the engineering and other related structures. In addition to these consequences, some advantages of the novel approach can be explained as follow: this novel approach (i) provides a good option to see the limits of the data on the plot because data visualisation is very important; (ii) has benefited both visually and mathematically in considering the extreme data, and (iii) can also be evaluated as a support test for other trend tests, such as MK and Sen.