Abstract: Site design improvement (SEO) is a critical issue for upgrading a site's perceivability with search motor outcomes.Web optimization issues, like Site Popularity, Content Quality, Keyword Density, and Publicity, were not considered duringthe website improvement measure. Hence, the recovery pace of the current strategies is lacking. In this examination,Triangular Fuzzy Deep Structured Learning-Based Predictive Page Ranking (TFDSL-PPR) Method is proposed to tacklethese restrictions. To start with, the TFDSL-PPR procedure takes various client inquiries as contribution to the informationlayer, and afterward it utilizes four secret layers to profoundly examine the website pages dependent on an info question. Theoriginally covered up layer decides the catchphrases from the client inquiry. The second secret layer measures the webpagenotoriety, content quality, catchphrase thickness and exposure of all website pages in the web crawler. It then, at that pointachieves Goodman and Kruskal's Gamma Predictive Ranking cycle in the third secret layer, where it positions the pages bythinking about their likenesses. The proposed TFDSL-PPR method is applied to the ClueWeb09 Dataset regarding anassortment of client inquiries. The outcomes are benchmarked by existing techniques based on a few measurements, forexample, recovery rate, time, and bogus positive rate.Keywords: —Deep Structured Learning, Filtering, Ranking, Search Engine, Site Popularity, Content Quality, Keyword Density,Publicity, Web pages.----------------------