MLwiN 為一套軟體擬合多級模型。MLwiN 的一個重要特點是它的圖形化介面。這些允許使用者輕鬆地設置，適合和操作模式。有的資料操作，繪製、 查看反覆運算等的進度視窗。可以直接使用直接連結到各類派生的類圖，作為模型參數的更改會自動更新的標準統計標記法指定擬合模型的預測。同樣後, 殘餘估計和它們的功能可以直接連結到圖形，例如為模型診斷程式。
多元模型很簡單，指定使用特別的輸入的螢幕。可以指定複雜的方差函數和該軟體將允許線性和非線性模型方面的差異作為解釋變數與互動的螢幕，其中顯示生成的模型的標準標記法表示的函數。
瑪律科夫鏈蒙特卡羅 (MCMC) 貝葉斯建模是詳細的視覺診斷與合併了。參數化 nd 非參數自舉是可用和反覆運算的引導已實施的無偏估計與多級廣義線性模型。

A software package for fitting multilevel models. An important feature of MLwiN is its graphical interfaces. These allow the user easily to set up, fit and manipulate models. There are windows for data manipulation, plotting, viewing the progress of iterations etc. Predictions from fitted models can be specified directly using standard statistical notation with direct links to various kinds of derived graphs, which are automatically updated as model parameters change. Likewise, posterior residual estimates and functions of them can be linked directly to graphs, for example for model diagnostics.

Multivariate models are simple to specify using a special input screen. Complex variance functions can be specified and the software will allow linear and non-linear modelling of variances as functions of explanatory variables with an interactive screen, which displays the resulting model in standard notation.
Markov Chain Monte Carlo (MCMC) Bayesian modelling is incorporated with detailed visual diagnostics. Parametric nd non-parametric bootstrapping is available and an iterated bootstrap has been implemented for unbiased estimation with multilevel generalised linear models.
　

A few of its features

Names window (where you can see all the variables)
Equations window (showing what model has been fitted and the parameter estimates). 
Variance function window (to calculate the residual variance at any level)
Predictions window (to calculate predicted values for each individual in the dataset, specifying what should be included in the prediction), and
Graphs (here the user has selected the country line that seems to be different from the others and asked that points relating to this country be drawn in red in all graphs, to help in deciding whether this is an outlier; the country is the Netherlands, as the user would have seen when they clicked on the line).