Changes in a language over time causes the texts that is written in old times contain lot of words that is not used at the present time. This makes it difficult for readers to understand old texts. The goal of text simplification task is to increase the readability and understandability of the text by preserving the meaning. In this study, it is aimed to reduce the complexity of the texts written in republican period Turkish with text simplification methods. First, a parallel dataset is build using Nutuk, then a statistical machine translation model is trained. The results are measured using BLEU metric that is used in evaluation of machine translation systems. With this work, the complexity of old texts is reduced and the target audience of these texts is increased.