A method and system for predicting a user activity level associated with an application. An activity level is a number of transactions performed by users utilizing the application per time period or a number of users utilizing the application per time period. Measurements of activity levels are assigned to a user activity metric (UAM) variable, and associated values are assigned to a set of factors. At least one correlation coefficient between each factor and the UAM is calculated. In response to a maximum correlation coefficient associated with a factor being less than a pre-defined threshold, the factor is excluded from the set of factors to facilitate forming a subset of factors associated with correlation coefficients whose absolute values are greater than or equal to the pre-defined threshold. A regression model utilizing the subset is generated to predict an activity level.

 
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