Student Performance Prediction Using Logistic Regression

📰 Medium · Machine Learning

Predict student performance using logistic regression with study hours, attendance, and marks as features

intermediate Published 9 May 2026
Action Steps
  1. Collect data on student study hours, attendance, and marks
  2. Preprocess the data by handling missing values and scaling features
  3. Train a logistic regression model using the collected data
  4. Evaluate the model's performance using metrics like accuracy and precision
  5. Deploy the model to predict student performance and identify areas for improvement
Who Needs to Know This

Data scientists and educators can benefit from this model to identify at-risk students and provide targeted support

Key Insight

💡 Logistic regression can be used to predict binary outcomes like student performance based on relevant features

Share This
Use logistic regression to predict student success based on study hours, attendance, and marks #MachineLearning #Education

Key Takeaways

Predict student performance using logistic regression with study hours, attendance, and marks as features

Full Article

Title: Student Performance Prediction Using Logistic Regression

URL Source: https://medium.com/@pinjarialeema3/student-performance-prediction-using-logistic-regression-dcdb910fbb6b?source=rss------machine_learning-5

Published Time: 2026-05-09T07:03:40Z

Markdown Content:
# Student Performance Prediction Using Logistic Regression | by Pinjarialeema | May, 2026 | Medium

[Sitemap](https://medium.com/sitemap/sitemap.xml)

[Open in app](https://play.google.com/store/apps/details?id=com.medium.reader&referrer=utm_source%3DmobileNavBar&source=post_page---top_nav_layout_nav-----------------------------------------)

Sign up

[Sign in](https://medium.com/m/signin?operation=login&redirect=https%3A%2F%2Fmedium.com%2F%40pinjarialeema3%2Fstudent-performance-prediction-using-logistic-regression-dcdb910fbb6b&source=post_page---top_nav_layout_nav-----------------------global_nav------------------)

[](https://medium.com/?source=post_page---top_nav_layout_nav-----------------------------------------)

Get app

[Write](https://medium.com/m/signin?operation=register&redirect=https%3A%2F%2Fmedium.com%2Fnew-story&source=---top_nav_layout_nav-----------------------new_post_topnav------------------)

[Search](https://medium.com/search?source=post_page---top_nav_layout_nav-----------------------------------------)

Sign up

[Sign in](https://medium.com/m/signin?operation=login&redirect=https%3A%2F%2Fmedium.com%2F%40pinjarialeema3%2Fstudent-performance-prediction-using-logistic-regression-dcdb910fbb6b&source=post_page---top_nav_layout_nav-----------------------global_nav------------------)

![Image 1](https://miro.medium.com/v2/resize:fill:32:32/1*dmbNkD5D-u45r44go_cf0g.png)

# Student Performance Prediction Using Logistic Regression

[![Image 2: Pinjarialeema](https://miro.medium.com/v2/da:true/resize:fill:32:32/0*OGnFvCts5QvsRoOC)](https://medium.com/@pinjarialeema3?source=post_page---byline--dcdb910fbb6b---------------------------------------)

[Pinjarialeema](https://medium.com/@pinjarialeema3?source=post_page---byline--dcdb910fbb6b---------------------------------------)

Follow

5 min read

·

1 hour ago

[](https://medium.com/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2F_%2Fvote%2Fp%2Fdcdb910fbb6b&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40pinjarialeema3%2Fstudent-performance-prediction-using-logistic-regression-dcdb910fbb6b&user=Pinjarialeema&userId=0ff266d56034&source=---header_actions--dcdb910fbb6b---------------------clap_footer------------------)

[](https://medium.com/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2F_%2Fbookmark%2Fp%2Fdcdb910fbb6b&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40pinjarialeema3%2Fstudent-performance-prediction-using-logistic-regression-dcdb910fbb6b&source=---header_actions--dcdb910fbb6b---------------------bookmark_footer------------------)

[Listen](https://medium.com/m/signin?actionUrl=https%3A%2F%2Fmedium.com%2Fplans%3Fdimension%3Dpost_audio_button%26postId%3Ddcdb910fbb6b&operation=register&redirect=https%3A%2F%2Fmedium.com%2F%40pinjarialeema3%2Fstudent-performance-prediction-using-logistic-regression-dcdb910fbb6b&source=---header_actions--dcdb910fbb6b---------------------post_audio_button------------------)

Share

_How Machine Learning Can Help Predict Student Success Using Study Hours, Attendance, and Marks_

Press enter or click to view image in full size

![Image 3](https://miro.medium.com/v2/resize:fit:700/1*1Jy2Yq8MjP4NtKgvVppMVQ.jpeg)

## Introduction

In today’s education system, predicting student performance has become an important challenge for schools and colleges. Teachers often struggle to identify students who may fail before the final exams. What if we could use Machine Learning to predict whether a student will pass or fail based on their academic behavior?

In this project, I built a complete Machine Learning classification model using Logistic Regression to predict student performance. The model uses features like:

* Study Hours
* Attendance Percentage
*
Read full article → ← Back to Reads