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Best Predictive Analytics Software 2026
Predictive analytics software helps teams build forecasts, evaluate models, automate machine learning and put predictions into use. This list is for buyers comparing those capabilities across hosted, self-hosted and code-based tools.
Compare the published free plan or trial, paid starting point, forecasting workflows, model evaluation, automated machine learning, deployment mode, time-series modeling, data connectors and API access. Platform labels cover web, Linux, API, self-hosted, Windows and macOS options.
KNIME Analytics Platform
The free desktop platform suits people building data workflows for personal use.
WindowsMacLinuxMLJAR AutoML
MLJAR AutoML automates supervised learning for tabular classification and regression in notebooks or Python scripts.
WebWindowsMac+2Neural Designer
Neural Designer builds, trains and deploys neural-network models through a no-code visual interface.
WindowsMacLinuxPyCaret
PyCaret suits Python users who want to automate model experiments across supported machine-learning tasks.
WebWindowsMac+3Weka is open-source machine-learning software distributed under the GNU General Public License.
Aible is designed for business users and enterprise teams, including people without specialized AI knowledge.
AutoGluon suits Python users building predictive models from tabular, time-series or multimodal data.
It may suit individuals, hobbyists, and non-profits seeking predictive models from structured data, as the Free plan is described for those audiences.
Oracle WebCenter Content manages enterprise content through web, desktop, mobile, Linux and API deployments.
Orange Data Mining uses connected widgets for visual data retrieval, modeling, evaluation and interactive charts.
Free library for automated machine learning, model tuning and LLM adaptation; runs through API, desktop or self-hosting.
Prophet forecasts time series with nonlinear trends, seasonality and holiday effects in Python or R.
TPOT uses genetic programming to optimize Python machine-learning pipelines for classifiers and regressors.
AI software for building, delivering and overseeing predictive, generative and agent-based systems on cloud or on-premises.
Business forecasting software that uses statistical models for seasonal, trend, cycle and promotion effects.
AI demand planning software for forecasting, collaborative review, KPIs, S&OP outputs and product lifecycles.
Anaplan is presented for organizations coordinating plans across functions such as finance, sales, supply chain, HR, and retail.
auto-sklearn automates model fitting and ensemble construction for classification and regression with scikit-learn.
Google search service for vector, keyword and combined queries in recommendations and generative AI apps.
Enterprise software for developing, operating, sharing and governing predictive, generative and agent-based AI.
Peak analyzes inventory and pricing data to recommend and execute business decisions with AI agents.
Demand-planning software forecasts SKU-level demand by day and aggregates views up to 24 months; runs on the web.
Before you choose
Check the way you can start
Review whether a tool has a free plan, a free trial or a paid starting point. BigML lists a free plan, a paid price from $1,000 per month and a three-day trial. Aible lists a 30-day trial and a paid price from $99 per user per month.
PyCaret, Weka, MLJAR AutoML and auto-sklearn list free or open-source pricing. Confirm licence terms before you plan code changes or redistribution.
Match the modeling work
Use the comparison fields to check forecasting workflows, time-series modeling and model evaluation. These fields help distinguish a tool for scheduled forecasts from one focused on broader machine-learning work.
Automated machine learning can reduce manual model setup. Check how that capability fits with the forecasting and evaluation steps your project requires.
Plan data and deployment
Compare deployment mode, data connectors and API access before choosing a workflow. A self-hosted option may suit a controlled environment, while web access or an API may fit a service that sends predictions to other software.
Platform labels identify support for web, Linux, API, self-hosted, Windows and macOS. Match those labels to the systems that will run your models and receive data.
Check the maker and product scope
Review the maker's product page for the exact scope of the tool and its current pricing terms. The list includes products from IBM, Oracle, Siemens, Amazon, KNIME and other makers.
For tools such as IBM Planning Analytics or Oracle WebCenter Content, confirm that the forecasting and analytics functions match your intended use rather than assuming the product name covers it.