In today’s digital world, information can very easily be accessed and digitally processed anywhere. Devices which are capable of processing digital data range from desktop computers to laptops, mobile phones, tablets, and personal digital assistants. For effective communication, text on a Web site should catch a reader’s attention and should be easy to both read and understand. Different constraints are associated with on-screen text readability and legibility, such as font size, color, and style, as well as foreground and background color contrast, line spacing, text congestion, vocabulary and grammar, but text recognition and comprehension are two of the major problems. In this study, we address the issue of how to enhance text readability for non-native English speakers who have a basic understanding of English language and speak local languages which are not formally taught in academia. We select a use case in Pakistan, a country in which English and Urdu are the official languages, and a number of local languages are spoken in different parts of the country. Due to the wide variety of local languages, no Web site can support the many local language scripts or alphabets and display them on digital devices. When users with only a basic knowledge of English—particularly low-literate users from a local language background—try to read an English text, it is highly challenging for them to understand the meaning of words. In this study, we propose a plain language scheme in which a text is converted into a roman text. A roman text is formed by using the English alphabet and combining letters in such a way that when it is read, it sounds like a local language. To evaluate the applicability of our approach, we conducted a survey of users from different educational backgrounds, using a text written in English, local and plain language from users who speak particular local language. For each survey, we took three to four paragraphs in English on general interest topics and translated it into local language and plain language. To measure the acceptability of each approach, we used five usability engineering attributes as a benchmark—efficiency, effectiveness, learnability, memorability, and satisfaction. From the results of the analysis, we observe that our proposed plain language scheme is more efficient, effective, learnable and memorable, and achieves a higher satisfaction level for low-literate users than two other languages.