This paper presents an application of multivariate proportional hazards model for birth interval that are clustered into geographical regions. Observations from same cluster usually share certain unobserved characteristics and as a result tend to be correlated. In multivariate proportional hazards model correlations among observations are considered. In analysis if associations among observations are ignored, standard error of the estimates of parameters of interest may be incorrect. Present research deals with the extension of the Cox proportional hazards model that allows for heterogeneity due to omitted covariates using frailty (random effect) approach, and there by uses a more general class of mixed-modeling that estimates predictors via parametric and non-parametric regression. In this study, Cox model and multivariate proportional hazards model are used for analyzing birth interval of Bangladesh using Bangladesh Demographic and Health Survey (BDHS, 2004) data. The result of this study indicates that, the unobserved cluster effect has a sizeable impact on birth interval in Bangladesh. Mothers’ education and mothers’ age has a significant effect on birth interval. The most important factor for birth interval is survival status of child. This study demonstrates how the factors affect the parents for having successive children in Bangladesh.