This paper aims to introduce a novel univariate probability distribution called the Weibull X-Lindley distribution (W-XLD), designed to be more flexible in modeling data with different patterns. The core idea behind this distribution arose to address some of the limitations of traditional distributions by introducing a form factor to increase flexibility to the proposed distributions. The technique used to construct W-XLD relies on multiplying the survival functions of the X-Lindley and Weibull distributions to find the W-XLD survival function. Based on this, the statistical functions of W-XLD were defined, including the cumulative distribution function (cdf), the probability density function (pdf), and the risk function. The shapes of the distribution functions for various conditional data and parameter values ​​were discussed. The distribution parameters are two: the shape parameter (β) and the scale parameter (ϑ). The properties of the density and risk functions at the boundaries of the random variable domain were examined, based on finding their boundary values. Furthermore, the basic and statistical characteristics were extracted, analyzed, given, and studied., including pattern, moments, kurtosis, skewness, variance, generated moments, quantiles, mean time to failure, and segmentation